Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(Sentiment analysis). Showing records 1 – 30 of 403 total matches.

[1] [2] [3] [4] [5] … [14]

Search Limiters

Last 2 Years | English Only

Department

Degrees

Levels

Languages

Country

▼ Search Limiters


University of Waterloo

1. Jiao, Yuwei. Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations.

Degree: 2018, University of Waterloo

 Sentiments and emotions play essential roles in small group interactions, especially in self-organized collaborative groups. Many people view sentiments as universal constructs; however, cultural differences… (more)

Subjects/Keywords: sentiment analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jiao, Y. (2018). Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14108

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jiao, Yuwei. “Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations.” 2018. Thesis, University of Waterloo. Accessed October 25, 2020. http://hdl.handle.net/10012/14108.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jiao, Yuwei. “Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations.” 2018. Web. 25 Oct 2020.

Vancouver:

Jiao Y. Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10012/14108.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jiao Y. Affect Lexicon Induction For the Github Subculture Using Distributed Word Representations. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/14108

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


San Jose State University

2. Grossfeld, Elena. Evaluating the Contribution of Hashtags to Sentiment Analysis of Microblogs.

Degree: MA, Linguistics, 2012, San Jose State University

  Microblogging has become the new and informal venue for communication and a main source of news and information for millions of users who subscribe… (more)

Subjects/Keywords: analysis; hashtag; microblog; sentiment; sentiment analysis; Twitter

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Grossfeld, E. (2012). Evaluating the Contribution of Hashtags to Sentiment Analysis of Microblogs. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.4fjb-3yzw ; https://scholarworks.sjsu.edu/etd_theses/4234

Chicago Manual of Style (16th Edition):

Grossfeld, Elena. “Evaluating the Contribution of Hashtags to Sentiment Analysis of Microblogs.” 2012. Masters Thesis, San Jose State University. Accessed October 25, 2020. https://doi.org/10.31979/etd.4fjb-3yzw ; https://scholarworks.sjsu.edu/etd_theses/4234.

MLA Handbook (7th Edition):

Grossfeld, Elena. “Evaluating the Contribution of Hashtags to Sentiment Analysis of Microblogs.” 2012. Web. 25 Oct 2020.

Vancouver:

Grossfeld E. Evaluating the Contribution of Hashtags to Sentiment Analysis of Microblogs. [Internet] [Masters thesis]. San Jose State University; 2012. [cited 2020 Oct 25]. Available from: https://doi.org/10.31979/etd.4fjb-3yzw ; https://scholarworks.sjsu.edu/etd_theses/4234.

Council of Science Editors:

Grossfeld E. Evaluating the Contribution of Hashtags to Sentiment Analysis of Microblogs. [Masters Thesis]. San Jose State University; 2012. Available from: https://doi.org/10.31979/etd.4fjb-3yzw ; https://scholarworks.sjsu.edu/etd_theses/4234


Cornell University

3. Yessenalina, Ainur. Exploiting Structure For Sentiment Classification.

Degree: PhD, Computer Science, 2012, Cornell University

 This thesis studies the problem of sentiment classification at both the document and sentence level using statistical learning methods. In particular, we develop computational models… (more)

Subjects/Keywords: sentiment classification; sentiment analysis; natural language processing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yessenalina, A. (2012). Exploiting Structure For Sentiment Classification. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/30982

Chicago Manual of Style (16th Edition):

Yessenalina, Ainur. “Exploiting Structure For Sentiment Classification.” 2012. Doctoral Dissertation, Cornell University. Accessed October 25, 2020. http://hdl.handle.net/1813/30982.

MLA Handbook (7th Edition):

Yessenalina, Ainur. “Exploiting Structure For Sentiment Classification.” 2012. Web. 25 Oct 2020.

Vancouver:

Yessenalina A. Exploiting Structure For Sentiment Classification. [Internet] [Doctoral dissertation]. Cornell University; 2012. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1813/30982.

Council of Science Editors:

Yessenalina A. Exploiting Structure For Sentiment Classification. [Doctoral Dissertation]. Cornell University; 2012. Available from: http://hdl.handle.net/1813/30982


University of Manchester

4. Qin, Zhenxin. A Framework and practical implementation for sentiment analysis and aspect exploration.

Degree: 2017, University of Manchester

 With the upsurge of Web 2.0, customers are able to share their opinions and feelings about products and services, politics, economic shifts, current events and… (more)

Subjects/Keywords: Sentiment analysis; aspect analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Qin, Z. (2017). A Framework and practical implementation for sentiment analysis and aspect exploration. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:308707

Chicago Manual of Style (16th Edition):

Qin, Zhenxin. “A Framework and practical implementation for sentiment analysis and aspect exploration.” 2017. Doctoral Dissertation, University of Manchester. Accessed October 25, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:308707.

MLA Handbook (7th Edition):

Qin, Zhenxin. “A Framework and practical implementation for sentiment analysis and aspect exploration.” 2017. Web. 25 Oct 2020.

Vancouver:

Qin Z. A Framework and practical implementation for sentiment analysis and aspect exploration. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2020 Oct 25]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:308707.

Council of Science Editors:

Qin Z. A Framework and practical implementation for sentiment analysis and aspect exploration. [Doctoral Dissertation]. University of Manchester; 2017. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:308707

5. Yoshida, Yasuhisa. Transfer Learning for Multiple-Domain Sentiment Analysis : 複数分野間における評判分析のための転移学習; フクスウ ブンヤカン ニ オケル ヒョウバン ブンセキ ノ タメ ノ テンイ ガクシュウ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: sentiment analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yoshida, Y. (n.d.). Transfer Learning for Multiple-Domain Sentiment Analysis : 複数分野間における評判分析のための転移学習; フクスウ ブンヤカン ニ オケル ヒョウバン ブンセキ ノ タメ ノ テンイ ガクシュウ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/7603

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yoshida, Yasuhisa. “Transfer Learning for Multiple-Domain Sentiment Analysis : 複数分野間における評判分析のための転移学習; フクスウ ブンヤカン ニ オケル ヒョウバン ブンセキ ノ タメ ノ テンイ ガクシュウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed October 25, 2020. http://hdl.handle.net/10061/7603.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yoshida, Yasuhisa. “Transfer Learning for Multiple-Domain Sentiment Analysis : 複数分野間における評判分析のための転移学習; フクスウ ブンヤカン ニ オケル ヒョウバン ブンセキ ノ タメ ノ テンイ ガクシュウ.” Web. 25 Oct 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Yoshida Y. Transfer Learning for Multiple-Domain Sentiment Analysis : 複数分野間における評判分析のための転移学習; フクスウ ブンヤカン ニ オケル ヒョウバン ブンセキ ノ タメ ノ テンイ ガクシュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10061/7603.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Yoshida Y. Transfer Learning for Multiple-Domain Sentiment Analysis : 複数分野間における評判分析のための転移学習; フクスウ ブンヤカン ニ オケル ヒョウバン ブンセキ ノ タメ ノ テンイ ガクシュウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/7603

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


University of Nairobi

6. Gitau, Eric. An approach for using twitter to perform sentiment analysis in Kenya .

Degree: 2011, University of Nairobi

 The interest in sentiment analysis as a research area has become increasingly popular with the development of new social interaction technologies. Twitter, being one of… (more)

Subjects/Keywords: twitter; sentiment analysis; Kenya

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gitau, E. (2011). An approach for using twitter to perform sentiment analysis in Kenya . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10196

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gitau, Eric. “An approach for using twitter to perform sentiment analysis in Kenya .” 2011. Thesis, University of Nairobi. Accessed October 25, 2020. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10196.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gitau, Eric. “An approach for using twitter to perform sentiment analysis in Kenya .” 2011. Web. 25 Oct 2020.

Vancouver:

Gitau E. An approach for using twitter to perform sentiment analysis in Kenya . [Internet] [Thesis]. University of Nairobi; 2011. [cited 2020 Oct 25]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10196.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gitau E. An approach for using twitter to perform sentiment analysis in Kenya . [Thesis]. University of Nairobi; 2011. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10196

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Guelph

7. Stantic, Daniel. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis.

Degree: MS, School of Computer Science, 2016, University of Guelph

 In this thesis, we develop a new probabilistic model for aspect-level sentiment analysis based on POSLDA, a topic classifier that incorporates syntax modelling for better… (more)

Subjects/Keywords: natural language processing; sentiment analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Stantic, D. (2016). A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616

Chicago Manual of Style (16th Edition):

Stantic, Daniel. “A Unified Probabilistic Model for Aspect-Level Sentiment Analysis.” 2016. Masters Thesis, University of Guelph. Accessed October 25, 2020. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616.

MLA Handbook (7th Edition):

Stantic, Daniel. “A Unified Probabilistic Model for Aspect-Level Sentiment Analysis.” 2016. Web. 25 Oct 2020.

Vancouver:

Stantic D. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. [Internet] [Masters thesis]. University of Guelph; 2016. [cited 2020 Oct 25]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616.

Council of Science Editors:

Stantic D. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. [Masters Thesis]. University of Guelph; 2016. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616


University of Ottawa

8. Poursepanj, Hamid. Sentiment Analysis of Data from Online Forums on the Newborn Genome Sequencing .

Degree: 2015, University of Ottawa

 In this thesis, we classified user comments posted on online forums related to “Newborn Genome Sequencing” (NGS). User comments were annotated as irrelevant, positive, negative,… (more)

Subjects/Keywords: Sentiment Analysis; Newborn Genome Sequencing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Poursepanj, H. (2015). Sentiment Analysis of Data from Online Forums on the Newborn Genome Sequencing . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/32393

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Poursepanj, Hamid. “Sentiment Analysis of Data from Online Forums on the Newborn Genome Sequencing .” 2015. Thesis, University of Ottawa. Accessed October 25, 2020. http://hdl.handle.net/10393/32393.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Poursepanj, Hamid. “Sentiment Analysis of Data from Online Forums on the Newborn Genome Sequencing .” 2015. Web. 25 Oct 2020.

Vancouver:

Poursepanj H. Sentiment Analysis of Data from Online Forums on the Newborn Genome Sequencing . [Internet] [Thesis]. University of Ottawa; 2015. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10393/32393.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Poursepanj H. Sentiment Analysis of Data from Online Forums on the Newborn Genome Sequencing . [Thesis]. University of Ottawa; 2015. Available from: http://hdl.handle.net/10393/32393

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

9. Visser, P. (author). “What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations.

Degree: 2013, Delft University of Technology

We conclude this report with a system design and proof-of-concept to show how an adaptable hybrid sentiment classification system is able to improve sentiment analysis(more)

Subjects/Keywords: sentiment analysis; hybrid classification

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Visser, P. (. (2013). “What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f61f53fe-86bd-426d-8843-1e67d1141bdd

Chicago Manual of Style (16th Edition):

Visser, P (author). ““What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations.” 2013. Masters Thesis, Delft University of Technology. Accessed October 25, 2020. http://resolver.tudelft.nl/uuid:f61f53fe-86bd-426d-8843-1e67d1141bdd.

MLA Handbook (7th Edition):

Visser, P (author). ““What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations.” 2013. Web. 25 Oct 2020.

Vancouver:

Visser P(. “What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations. [Internet] [Masters thesis]. Delft University of Technology; 2013. [cited 2020 Oct 25]. Available from: http://resolver.tudelft.nl/uuid:f61f53fe-86bd-426d-8843-1e67d1141bdd.

Council of Science Editors:

Visser P(. “What do they say about us on Twitter?”: Hybrid sentiment retrieval for organisations. [Masters Thesis]. Delft University of Technology; 2013. Available from: http://resolver.tudelft.nl/uuid:f61f53fe-86bd-426d-8843-1e67d1141bdd


California State University – Sacramento

10. Kaur, Savleen. Opinion mining on social media.

Degree: MS, Computer Science, 2017, California State University – Sacramento

 The opinions and sentiments behind all the posts, comments and statuses shared on social media nowadays can be considered as a useful indicator for many… (more)

Subjects/Keywords: Twitter; Sentiment analysis; Data mining

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kaur, S. (2017). Opinion mining on social media. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/190550

Chicago Manual of Style (16th Edition):

Kaur, Savleen. “Opinion mining on social media.” 2017. Masters Thesis, California State University – Sacramento. Accessed October 25, 2020. http://hdl.handle.net/10211.3/190550.

MLA Handbook (7th Edition):

Kaur, Savleen. “Opinion mining on social media.” 2017. Web. 25 Oct 2020.

Vancouver:

Kaur S. Opinion mining on social media. [Internet] [Masters thesis]. California State University – Sacramento; 2017. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10211.3/190550.

Council of Science Editors:

Kaur S. Opinion mining on social media. [Masters Thesis]. California State University – Sacramento; 2017. Available from: http://hdl.handle.net/10211.3/190550


University of Texas – Austin

11. Chen, Jiajun, M.S. in Statistics. Search engine For Twitter sentiment analysis.

Degree: MSin Statistics, Statistics, 2015, University of Texas – Austin

 The purpose of sentiment analysis is to determine the attitude of a writer or a speaker with respect to some topic or his feeling in… (more)

Subjects/Keywords: Twitter; Sentiment analysis; Search engine

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chen, Jiajun, M. S. i. S. (2015). Search engine For Twitter sentiment analysis. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32489

Chicago Manual of Style (16th Edition):

Chen, Jiajun, M S in Statistics. “Search engine For Twitter sentiment analysis.” 2015. Masters Thesis, University of Texas – Austin. Accessed October 25, 2020. http://hdl.handle.net/2152/32489.

MLA Handbook (7th Edition):

Chen, Jiajun, M S in Statistics. “Search engine For Twitter sentiment analysis.” 2015. Web. 25 Oct 2020.

Vancouver:

Chen, Jiajun MSiS. Search engine For Twitter sentiment analysis. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/2152/32489.

Council of Science Editors:

Chen, Jiajun MSiS. Search engine For Twitter sentiment analysis. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32489


University of Waterloo

12. Fu, Chengyao. Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets.

Degree: 2020, University of Waterloo

Sentiment analysis has been widely used in the domain of finance. There are two most common textual sentiment analysis methods in finance: it{dictionary-based approach} and… (more)

Subjects/Keywords: sentiment analysis; natural language processing; finance; sentiment dictionary; sentiment lexicon induction; multiple-instance learning; stocks

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fu, C. (2020). Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/16382

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Fu, Chengyao. “Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets.” 2020. Thesis, University of Waterloo. Accessed October 25, 2020. http://hdl.handle.net/10012/16382.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Fu, Chengyao. “Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets.” 2020. Web. 25 Oct 2020.

Vancouver:

Fu C. Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10012/16382.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fu C. Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/16382

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Alberta

13. Dergacheva, Elena L. Text analysis of Maxpark and LiveJournal Russia: How is the evaluation of modern femininity and masculinity discussed in Russian blogs.

Degree: MA, Department of Modern Languages and Cultural Studies Humanities Computing, 2014, University of Alberta

 This thesis focuses on text analysis of Russian speaking blogs with the goal to examine critically discussions of femininity and masculinity in modern Russian society.… (more)

Subjects/Keywords: sentiment analysis; text analysis, blogs; gender studies

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Dergacheva, E. L. (2014). Text analysis of Maxpark and LiveJournal Russia: How is the evaluation of modern femininity and masculinity discussed in Russian blogs. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/vm40xs42f

Chicago Manual of Style (16th Edition):

Dergacheva, Elena L. “Text analysis of Maxpark and LiveJournal Russia: How is the evaluation of modern femininity and masculinity discussed in Russian blogs.” 2014. Masters Thesis, University of Alberta. Accessed October 25, 2020. https://era.library.ualberta.ca/files/vm40xs42f.

MLA Handbook (7th Edition):

Dergacheva, Elena L. “Text analysis of Maxpark and LiveJournal Russia: How is the evaluation of modern femininity and masculinity discussed in Russian blogs.” 2014. Web. 25 Oct 2020.

Vancouver:

Dergacheva EL. Text analysis of Maxpark and LiveJournal Russia: How is the evaluation of modern femininity and masculinity discussed in Russian blogs. [Internet] [Masters thesis]. University of Alberta; 2014. [cited 2020 Oct 25]. Available from: https://era.library.ualberta.ca/files/vm40xs42f.

Council of Science Editors:

Dergacheva EL. Text analysis of Maxpark and LiveJournal Russia: How is the evaluation of modern femininity and masculinity discussed in Russian blogs. [Masters Thesis]. University of Alberta; 2014. Available from: https://era.library.ualberta.ca/files/vm40xs42f


NSYSU

14. Chang, Chia-Chen. The Research of Constructing Domain-Specific Chinese Sentiment Lexicon.

Degree: Master, Information Management, 2018, NSYSU

 With the booming of social media, users generate a large number of texts, such as tweets, blogs, and comments, which are full of potential sentiment.… (more)

Subjects/Keywords: text mining; sentiment analysis; Chinese sentiment lexicon; word embedding; label propagation

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chang, C. (2018). The Research of Constructing Domain-Specific Chinese Sentiment Lexicon. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721118-153855

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chang, Chia-Chen. “The Research of Constructing Domain-Specific Chinese Sentiment Lexicon.” 2018. Thesis, NSYSU. Accessed October 25, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721118-153855.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chang, Chia-Chen. “The Research of Constructing Domain-Specific Chinese Sentiment Lexicon.” 2018. Web. 25 Oct 2020.

Vancouver:

Chang C. The Research of Constructing Domain-Specific Chinese Sentiment Lexicon. [Internet] [Thesis]. NSYSU; 2018. [cited 2020 Oct 25]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721118-153855.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chang C. The Research of Constructing Domain-Specific Chinese Sentiment Lexicon. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721118-153855

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Manchester

15. Alhazmi, Samah. Linking Arabic social media based on similarity and sentiment.

Degree: PhD, 2016, University of Manchester

 A large proportion of World Wide Web (WWW) users treat it as a social medium, i.e. many of them use the WWW to express and… (more)

Subjects/Keywords: 302.23; Opinion mining; Sentiment analysis; Arabic; Social media; Sentiment classification

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Alhazmi, S. (2016). Linking Arabic social media based on similarity and sentiment. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/linking-arabic-social-media-based-on-similarity-and-sentiment(04288028-707c-46f2-a028-8ee3066dfa89).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727880

Chicago Manual of Style (16th Edition):

Alhazmi, Samah. “Linking Arabic social media based on similarity and sentiment.” 2016. Doctoral Dissertation, University of Manchester. Accessed October 25, 2020. https://www.research.manchester.ac.uk/portal/en/theses/linking-arabic-social-media-based-on-similarity-and-sentiment(04288028-707c-46f2-a028-8ee3066dfa89).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727880.

MLA Handbook (7th Edition):

Alhazmi, Samah. “Linking Arabic social media based on similarity and sentiment.” 2016. Web. 25 Oct 2020.

Vancouver:

Alhazmi S. Linking Arabic social media based on similarity and sentiment. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2020 Oct 25]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/linking-arabic-social-media-based-on-similarity-and-sentiment(04288028-707c-46f2-a028-8ee3066dfa89).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727880.

Council of Science Editors:

Alhazmi S. Linking Arabic social media based on similarity and sentiment. [Doctoral Dissertation]. University of Manchester; 2016. Available from: https://www.research.manchester.ac.uk/portal/en/theses/linking-arabic-social-media-based-on-similarity-and-sentiment(04288028-707c-46f2-a028-8ee3066dfa89).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727880


Linnaeus University

16. Gustafsson, Marcus. Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules.

Degree: computer science and media technology (CM), 2020, Linnaeus University

Sentiment Analysis refers to the extraction of opinion and emotion from data. In its simplest form, an application estimates a sentence and labels it… (more)

Subjects/Keywords: Sentiment Analysis; Opinion Mining; Sentiment Lexicon; Swedish; Computer Sciences; Datavetenskap (datalogi)

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gustafsson, M. (2020). Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules. (Thesis). Linnaeus University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-91832

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gustafsson, Marcus. “Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules.” 2020. Thesis, Linnaeus University. Accessed October 25, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-91832.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gustafsson, Marcus. “Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules.” 2020. Web. 25 Oct 2020.

Vancouver:

Gustafsson M. Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules. [Internet] [Thesis]. Linnaeus University; 2020. [cited 2020 Oct 25]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-91832.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gustafsson M. Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules. [Thesis]. Linnaeus University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-91832

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

17. Razoux Schultz, Lex (author). Distance Based Source Domain Selection for Automated Sentiment Classification.

Degree: 2018, Delft University of Technology

Automated Sentiment Classification (SC) on short text fragments has been an upcoming field of research. Different machine learning techniques and word representation models have proven… (more)

Subjects/Keywords: sentiment analysis; sentiment classification; domain adaptation; source selection; domain selection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Razoux Schultz, L. (. (2018). Distance Based Source Domain Selection for Automated Sentiment Classification. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196

Chicago Manual of Style (16th Edition):

Razoux Schultz, Lex (author). “Distance Based Source Domain Selection for Automated Sentiment Classification.” 2018. Masters Thesis, Delft University of Technology. Accessed October 25, 2020. http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196.

MLA Handbook (7th Edition):

Razoux Schultz, Lex (author). “Distance Based Source Domain Selection for Automated Sentiment Classification.” 2018. Web. 25 Oct 2020.

Vancouver:

Razoux Schultz L(. Distance Based Source Domain Selection for Automated Sentiment Classification. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 25]. Available from: http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196.

Council of Science Editors:

Razoux Schultz L(. Distance Based Source Domain Selection for Automated Sentiment Classification. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196


NSYSU

18. Li, Jih-Pin. Explore Internet Users in Taiwan Neighbors Emotion.

Degree: Master, Information Management, 2014, NSYSU

 Traditional political science research usually adopts random sampling to choose a number of subjects and inquires their opinions towards certain issues. The result is then… (more)

Subjects/Keywords: LDA; political science; sentiment analysis; text mining

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Li, J. (2014). Explore Internet Users in Taiwan Neighbors Emotion. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0614114-062227

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Jih-Pin. “Explore Internet Users in Taiwan Neighbors Emotion.” 2014. Thesis, NSYSU. Accessed October 25, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0614114-062227.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Jih-Pin. “Explore Internet Users in Taiwan Neighbors Emotion.” 2014. Web. 25 Oct 2020.

Vancouver:

Li J. Explore Internet Users in Taiwan Neighbors Emotion. [Internet] [Thesis]. NSYSU; 2014. [cited 2020 Oct 25]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0614114-062227.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li J. Explore Internet Users in Taiwan Neighbors Emotion. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0614114-062227

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


UCLA

19. Tavabi, Leili Leili. Evaluation of Political Sentiment on Twitter.

Degree: Computer Science, 2015, UCLA

 With the increasing level of access to online political discourses, made possibleby the social media networks, a systematic analysis of political speech becomesmore critical. The… (more)

Subjects/Keywords: Computer science; Communication; Politics; Sentiment Analysis; Twitter

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tavabi, L. L. (2015). Evaluation of Political Sentiment on Twitter. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/5j82j35h

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tavabi, Leili Leili. “Evaluation of Political Sentiment on Twitter.” 2015. Thesis, UCLA. Accessed October 25, 2020. http://www.escholarship.org/uc/item/5j82j35h.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tavabi, Leili Leili. “Evaluation of Political Sentiment on Twitter.” 2015. Web. 25 Oct 2020.

Vancouver:

Tavabi LL. Evaluation of Political Sentiment on Twitter. [Internet] [Thesis]. UCLA; 2015. [cited 2020 Oct 25]. Available from: http://www.escholarship.org/uc/item/5j82j35h.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tavabi LL. Evaluation of Political Sentiment on Twitter. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/5j82j35h

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of North Texas

20. Wei, Jinliang. Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data.

Degree: 2019, University of North Texas

 Consumer's opinions and sentiments on products can reflect the performance of products in general or in various aspects. Analyzing these data is becoming feasible, considering… (more)

Subjects/Keywords: Aspect-based Sentiment Analysis; Information retrieval system

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wei, J. (2019). Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc1505264/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wei, Jinliang. “Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data.” 2019. Thesis, University of North Texas. Accessed October 25, 2020. https://digital.library.unt.edu/ark:/67531/metadc1505264/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wei, Jinliang. “Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data.” 2019. Web. 25 Oct 2020.

Vancouver:

Wei J. Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data. [Internet] [Thesis]. University of North Texas; 2019. [cited 2020 Oct 25]. Available from: https://digital.library.unt.edu/ark:/67531/metadc1505264/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wei J. Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data. [Thesis]. University of North Texas; 2019. Available from: https://digital.library.unt.edu/ark:/67531/metadc1505264/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

21. Chen, Bi. Topic Oriented Evolution and Sentiment Analysis.

Degree: 2011, Penn State University

 Topic modeling techniques help people to understand what is talking about in a corpus, and dramatically improve human’s work on academic or business productivity. Although… (more)

Subjects/Keywords: text mining; topic modeling; sentiment analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chen, B. (2011). Topic Oriented Evolution and Sentiment Analysis. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/11743

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chen, Bi. “Topic Oriented Evolution and Sentiment Analysis.” 2011. Thesis, Penn State University. Accessed October 25, 2020. https://submit-etda.libraries.psu.edu/catalog/11743.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chen, Bi. “Topic Oriented Evolution and Sentiment Analysis.” 2011. Web. 25 Oct 2020.

Vancouver:

Chen B. Topic Oriented Evolution and Sentiment Analysis. [Internet] [Thesis]. Penn State University; 2011. [cited 2020 Oct 25]. Available from: https://submit-etda.libraries.psu.edu/catalog/11743.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen B. Topic Oriented Evolution and Sentiment Analysis. [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/11743

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

22. Alhothali, Areej. A Socio-mathematical and Structure-Based Approach to Model Sentiment Dynamics in Event-Based Text.

Degree: 2017, University of Waterloo

 Natural language texts are often meant to express or impact the emotions of individuals. Recognizing the underlying emotions expressed in or triggered by textual content… (more)

Subjects/Keywords: Sentiment analysis; Natural language processing; Machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Alhothali, A. (2017). A Socio-mathematical and Structure-Based Approach to Model Sentiment Dynamics in Event-Based Text. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12480

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Alhothali, Areej. “A Socio-mathematical and Structure-Based Approach to Model Sentiment Dynamics in Event-Based Text.” 2017. Thesis, University of Waterloo. Accessed October 25, 2020. http://hdl.handle.net/10012/12480.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Alhothali, Areej. “A Socio-mathematical and Structure-Based Approach to Model Sentiment Dynamics in Event-Based Text.” 2017. Web. 25 Oct 2020.

Vancouver:

Alhothali A. A Socio-mathematical and Structure-Based Approach to Model Sentiment Dynamics in Event-Based Text. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10012/12480.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alhothali A. A Socio-mathematical and Structure-Based Approach to Model Sentiment Dynamics in Event-Based Text. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12480

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Wayne State University

23. Zhang, Jingwei. Multi-Way Factorization Machine For Sentiment Analysis.

Degree: MS, Computer Science, 2017, Wayne State University

Sentiment analysis is a process of learning the relationship between sentiment label and text. The research value of sentiment analysis is two-fold: first, it… (more)

Subjects/Keywords: Factorization Machine; Sentiment analysis; Computer Sciences

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, J. (2017). Multi-Way Factorization Machine For Sentiment Analysis. (Masters Thesis). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_theses/599

Chicago Manual of Style (16th Edition):

Zhang, Jingwei. “Multi-Way Factorization Machine For Sentiment Analysis.” 2017. Masters Thesis, Wayne State University. Accessed October 25, 2020. https://digitalcommons.wayne.edu/oa_theses/599.

MLA Handbook (7th Edition):

Zhang, Jingwei. “Multi-Way Factorization Machine For Sentiment Analysis.” 2017. Web. 25 Oct 2020.

Vancouver:

Zhang J. Multi-Way Factorization Machine For Sentiment Analysis. [Internet] [Masters thesis]. Wayne State University; 2017. [cited 2020 Oct 25]. Available from: https://digitalcommons.wayne.edu/oa_theses/599.

Council of Science Editors:

Zhang J. Multi-Way Factorization Machine For Sentiment Analysis. [Masters Thesis]. Wayne State University; 2017. Available from: https://digitalcommons.wayne.edu/oa_theses/599


University of Houston

24. -7251-2238. Computational Methods for Tweet Summarization and Emotion Extraction.

Degree: MS, Computer Science, 2020, University of Houston

 The process of gathering insights from social media has gained significant importance in the last decade. Since social media data is growing larger and larger,… (more)

Subjects/Keywords: NLP; Twitter Analytics; Tweet Summarization; Sentiment Analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-7251-2238. (2020). Computational Methods for Tweet Summarization and Emotion Extraction. (Masters Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/6617

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-7251-2238. “Computational Methods for Tweet Summarization and Emotion Extraction.” 2020. Masters Thesis, University of Houston. Accessed October 25, 2020. http://hdl.handle.net/10657/6617.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-7251-2238. “Computational Methods for Tweet Summarization and Emotion Extraction.” 2020. Web. 25 Oct 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7251-2238. Computational Methods for Tweet Summarization and Emotion Extraction. [Internet] [Masters thesis]. University of Houston; 2020. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10657/6617.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7251-2238. Computational Methods for Tweet Summarization and Emotion Extraction. [Masters Thesis]. University of Houston; 2020. Available from: http://hdl.handle.net/10657/6617

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Universidade Nova

25. Twanabasu, Bikesh. Sentiment analysis in geo social streams by using machine learning technique.

Degree: 2018, Universidade Nova

 Massive amounts of sentiment rich data are generated on social media in the form of Tweets, status updates, blog post, reviews, etc. Different people and… (more)

Subjects/Keywords: Geovisualization; Machine Learning; Opinion Mining; Sentiment Analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Twanabasu, B. (2018). Sentiment analysis in geo social streams by using machine learning technique. (Thesis). Universidade Nova. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/33797

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Twanabasu, Bikesh. “Sentiment analysis in geo social streams by using machine learning technique.” 2018. Thesis, Universidade Nova. Accessed October 25, 2020. https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/33797.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Twanabasu, Bikesh. “Sentiment analysis in geo social streams by using machine learning technique.” 2018. Web. 25 Oct 2020.

Vancouver:

Twanabasu B. Sentiment analysis in geo social streams by using machine learning technique. [Internet] [Thesis]. Universidade Nova; 2018. [cited 2020 Oct 25]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/33797.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Twanabasu B. Sentiment analysis in geo social streams by using machine learning technique. [Thesis]. Universidade Nova; 2018. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/33797

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Manitoba

26. Naqvi, Mohammed Moosa. Relationship discovery of price movements between sentiment analysis on social media data and stock market.

Degree: Computer Science, 2019, University of Manitoba

 A desire to make a profit on investment has been a prominent motivational factor in financial investments. The idea of growing with a blue chip… (more)

Subjects/Keywords: Machine Learning; Sentiment Analysis; Computational Finance

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Naqvi, M. M. (2019). Relationship discovery of price movements between sentiment analysis on social media data and stock market. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/34125

Chicago Manual of Style (16th Edition):

Naqvi, Mohammed Moosa. “Relationship discovery of price movements between sentiment analysis on social media data and stock market.” 2019. Masters Thesis, University of Manitoba. Accessed October 25, 2020. http://hdl.handle.net/1993/34125.

MLA Handbook (7th Edition):

Naqvi, Mohammed Moosa. “Relationship discovery of price movements between sentiment analysis on social media data and stock market.” 2019. Web. 25 Oct 2020.

Vancouver:

Naqvi MM. Relationship discovery of price movements between sentiment analysis on social media data and stock market. [Internet] [Masters thesis]. University of Manitoba; 2019. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1993/34125.

Council of Science Editors:

Naqvi MM. Relationship discovery of price movements between sentiment analysis on social media data and stock market. [Masters Thesis]. University of Manitoba; 2019. Available from: http://hdl.handle.net/1993/34125


Florida International University

27. Xue, Wei. Aspect Based Sentiment Analysis On Review Data.

Degree: PhD, Computer Science, 2017, Florida International University

  With proliferation of user-generated reviews, new opportunities and challenges arise. The advance of Web technologies allows people to access a large amount of reviews… (more)

Subjects/Keywords: sentiment analysis; text mining; Computer Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Xue, W. (2017). Aspect Based Sentiment Analysis On Review Data. (Doctoral Dissertation). Florida International University. Retrieved from https://digitalcommons.fiu.edu/etd/3721 ; 10.25148/etd.FIDC004076 ; FIDC004076

Chicago Manual of Style (16th Edition):

Xue, Wei. “Aspect Based Sentiment Analysis On Review Data.” 2017. Doctoral Dissertation, Florida International University. Accessed October 25, 2020. https://digitalcommons.fiu.edu/etd/3721 ; 10.25148/etd.FIDC004076 ; FIDC004076.

MLA Handbook (7th Edition):

Xue, Wei. “Aspect Based Sentiment Analysis On Review Data.” 2017. Web. 25 Oct 2020.

Vancouver:

Xue W. Aspect Based Sentiment Analysis On Review Data. [Internet] [Doctoral dissertation]. Florida International University; 2017. [cited 2020 Oct 25]. Available from: https://digitalcommons.fiu.edu/etd/3721 ; 10.25148/etd.FIDC004076 ; FIDC004076.

Council of Science Editors:

Xue W. Aspect Based Sentiment Analysis On Review Data. [Doctoral Dissertation]. Florida International University; 2017. Available from: https://digitalcommons.fiu.edu/etd/3721 ; 10.25148/etd.FIDC004076 ; FIDC004076

28. Wei, Miao. Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English.

Degree: 2017, RIAN

 With the increasing popularity of opinion-rich resources, opinion mining and sentiment analysis has received increasing attention. Sentiment analysis is one of the most effective ways… (more)

Subjects/Keywords: Sentiment Analysis; Deep Learning; Comparison; Chinese; English

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wei, M. (2017). Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English. (Thesis). RIAN. Retrieved from http://eprints.maynoothuniversity.ie/9903/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wei, Miao. “Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English.” 2017. Thesis, RIAN. Accessed October 25, 2020. http://eprints.maynoothuniversity.ie/9903/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wei, Miao. “Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English.” 2017. Web. 25 Oct 2020.

Vancouver:

Wei M. Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English. [Internet] [Thesis]. RIAN; 2017. [cited 2020 Oct 25]. Available from: http://eprints.maynoothuniversity.ie/9903/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wei M. Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English. [Thesis]. RIAN; 2017. Available from: http://eprints.maynoothuniversity.ie/9903/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

29. Kreuk, Laura (author). Sentiment Analysis: a comparison of feature sets for social data and reviews.

Degree: 2018, Delft University of Technology

Consumers share their experiences or opinion about products or brands in various channels nowadays, for example on review websites or social media. Sentiment analysis is… (more)

Subjects/Keywords: Sentiment Analysis; feature extraction; reviews; social data

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kreuk, L. (. (2018). Sentiment Analysis: a comparison of feature sets for social data and reviews. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97

Chicago Manual of Style (16th Edition):

Kreuk, Laura (author). “Sentiment Analysis: a comparison of feature sets for social data and reviews.” 2018. Masters Thesis, Delft University of Technology. Accessed October 25, 2020. http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97.

MLA Handbook (7th Edition):

Kreuk, Laura (author). “Sentiment Analysis: a comparison of feature sets for social data and reviews.” 2018. Web. 25 Oct 2020.

Vancouver:

Kreuk L(. Sentiment Analysis: a comparison of feature sets for social data and reviews. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 25]. Available from: http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97.

Council of Science Editors:

Kreuk L(. Sentiment Analysis: a comparison of feature sets for social data and reviews. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97

30. Wei, Miao. Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English.

Degree: 2017, RIAN

 With the increasing popularity of opinion-rich resources, opinion mining and sentiment analysis has received increasing attention. Sentiment analysis is one of the most effective ways… (more)

Subjects/Keywords: Sentiment Analysis; Deep Learning; Comparison; Chinese; English

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wei, M. (2017). Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English. (Thesis). RIAN. Retrieved from http://mural.maynoothuniversity.ie/9903/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wei, Miao. “Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English.” 2017. Thesis, RIAN. Accessed October 25, 2020. http://mural.maynoothuniversity.ie/9903/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wei, Miao. “Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English.” 2017. Web. 25 Oct 2020.

Vancouver:

Wei M. Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English. [Internet] [Thesis]. RIAN; 2017. [cited 2020 Oct 25]. Available from: http://mural.maynoothuniversity.ie/9903/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wei M. Sentiment Analysis Using Deep Learning: A Comparison Between Chinese And English. [Thesis]. RIAN; 2017. Available from: http://mural.maynoothuniversity.ie/9903/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

[1] [2] [3] [4] [5] … [14]

.