Data-Driven Content Analysis of Social Media: A Systematic Overview of Automated Methods

Annals of the American Academy of Political and Social Science

Volumn 659, Issue 1, 2015, Pages 78-94

  Schwartz, H Andrew ^a,b   Ungar, Lyle H ^b  

^a STONY BROOK UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

content analysis; Facebook; social media; text mining; Twitter

Indexed keywords

EID: 84927130833     PISSN: 00027162     EISSN: 15523349     Source Type: Journal    
DOI: 10.1177/0002716215569197     Document Type: Article

References (48)

1. Benjamini Yoav,Hochberg Yosef.Controlling the false discovery rate: A practical and powerful approach to multiple testing.Journal of the Royal Statistical Society. Series B (Methodological). 1995;57 (1): 289-300
2. Berinsky Adam J.,Huber Gregory A.,Lenz Gabriel S.Evaluating online labor markets for experimental research: Amazon.com’s Mechanical Turk.Political Analysis. 2012;20 (3): 351-68
3. Bishop Christopher M.Pattern recognition and machine learning. New York, NY: Springer; 2006:
4. Blei David M.,Ng Andrew Y.,Jordan Michael I.Latent dirichlet allocation.Journal of Machine Learning Research. 2003;3:993-1022
5. Bollen Johan,Mao Huina,Zeng Xiaojun.Twitter mood predicts the stock market.Journal of Computational Science. 2011;2 (1): 1-8
6. Bradley Margaret M.,Lang Peter J.Affective norms for English words (ANEW): Instruction manual and affective ratings. Gainesville, FL: The Center for Research in Psychophysiology, University of Florida; 1999:
7. Church Kenneth Ward,Hanks Patrick.Word association norms, mutual information, and lexicography.Computational Linguistics. 1990;16 (1): 22-29
8. Coltheart Max.The MRC psycholinguistic database.Quarterly Journal of Experimental Psychology. 1981;33 (4): 497-505
9. De ChoudhuryMunmunGamonMichaelCountsScottHorvitzEric. 2013. Predicting depression via social media. In Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media. Available from http://www.aaai.org.
10. Dodds Peter Sheridan,Harris Kameron Decker,Kloumann Isabel M.,Bliss Catherine A.,Danforth Christopher M.Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter.PloS One. 2011;:
11. Eichstaedt Johannes C.,Schwartz Andrew H.,Kern Margaret L.,Park Gregory J.,Labarthe Darwin,Merchant Raina,Jha Sneha,Agrawal Megha,Dziurzynski Lukasz,Sap Maarten, et al.Psychological language on Twitter predicts county-level heart disease mortality.Psychological Science. Forthcoming;:
12. Eisenstein Jacob,Smith Noah A.,Xing Eric P.Discovering sociolinguistic associations with structured sparsity.Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies; 2011; 2011. 1365.
13. George Alexander L.Propaganda analysis: A study of inferences made from Nazi propaganda in World War II. New York, NY: Row, Peterson, and Company; 1959:
14. Gerber Matthew S.Predicting crime using Twitter and kernel density estimation.Decision Support Systems. 2014;61:115-25
15. Ginsberg Jeremy,Mohebbi Matthew H.,Patel Rajan S.,Brammer Lynnette,Smolinski Mark S.,Brilliant Larry.Detecting influenza epidemics using search engine query data.Nature. 2009;457 (7232): 1012-14
16. Gosling Samuel D.,Vazire Simine,Srivastava Sanjay,John Oliver P.Should we trust web-based studies? A comparative analysis of six preconceptions about Internet questionnaires.American Psychologist. 2004;59 (2): 93-104
17. Graham Jesse,Haidt Jonathan,Nosek Brian A.Liberals and conservatives rely on different sets of moral foundations.Journal of Personality and Social Psychology. 2009;96 (5): 1029-46
18. Grimmer Justin,Stewart Brandon M.Text as data: The promise and pitfalls of automatic content analysis methods for political texts.Political Analysis. 2013;21 (3): 267-97
19. Hastie Trevor,Tibshirani Robert,Friedman JeromeThe elements of statistical learning. New York, NY: Springer; 2009:
20. Ireland Molly E.,Slatcher Richard B.,Eastwick Paul W.,Scissors Lauren E.,Finkel Eli J.,Pennebaker James W.Language style matching predicts relationship initiation and stability.Psychological Science. 2011;22 (1): 39-44
21. Jurafsky Daniel,Martin James H.Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition. Upper Saddle River, NJ: Prentice Hall; 2000:
22. Kramer Gerald H.The ecological fallacy revisited: Aggregate-versus individual-level findings on economics and elections, and sociotropic voting.American Political Science Review. 1983;77 (1): 92-111
23. Krippendorff KlausContent analysis: An introduction to its methodology. Thousand Oaks, CA: Sage Publications; 2012:
24. Laver Michael,Benoit Kenneth,Garry John.Extracting policy positions from political texts using words as data.American Political Science Review. 2003;97 (2): 311-31
25. Mairesse François,Walker Marilyn A.,Mehl Matthias R.,Moore Roger K.Using linguistic cues for the automatic recognition of personality in conversation and text.Journal of Artificial Intelligence Research (JAIR). 2007;30:457-500
26. Mehl Matthias R.,Robbins Megan L.Handbook of research methods for studying daily life. Mehl Matthias R.Conner Tamlin S., ed. New York, NY: Guilford Press; 2012:176-92.
27. Mitchell Lewis,Frank Morgan R.,Harris Kameron Decker,Dodds Peter Sheridan,Danforth Christopher M.The geography of happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place.PloS One. 2013;:
28. Monroe Burt L.,Colaresi Michael P.,Quinn Kevin M.Fightin’ words: Lexical feature selection and evaluation for identifying the content of political conflict.Political Analysis. 2008;16 (4): 372-403
29. Newman Matthew L.,Groom Carla J.,Handelman Lori D.,Pennebaker James W.Gender differences in language use: An analysis of 14,000 text samples.Discourse Processes. 2008;45 (3): 211-36
30. O’Connor Brendan,Balasubramanyan Ramnath,Routledge Bryan R.,Smith Noah A.From tweets to polls: Linking text sentiment to public opinion time series.ICWSM. 2010;11:122-29
31. Pang Bo,Lee Lillian.Opinion mining and sentiment analysis.Foundations and Trends in Information Retrieval. 2008;2 (1–2): 1-135
32. Pang Bo,Lee Lillian,Vaithyanathan Shivakumar.Thumbs up? Sentiment classification using machine learning techniques.Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing; 2002; 2002. 79.
33. PaulMichael J.DredzeMark. 2011. You are what you tweet: Analyzing Twitter for public health. In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media. Available from http://www.aaai.org.
34. Pennebaker James W.,Chung Cindy K.,Ireland Molly,Gonzales Amy,Booth Roger J.The development and psychometric properties of LIWC2007.LIWCNET. 2007;1:1-22
35. Pennebaker James W.,Francis Martha E.,Booth Roger J.Linguistic inquiry and word count: LIWC 2001. Mahwah, NJ: Lawrence Erlbaum Associates; 2001:
36. Pennebaker James W.,Stone Lori D.Words of wisdom: Language use over the life span.Journal of Personality and Social Psychology. 2003;85 (2): 291-301
37. Peterson Christopher,Seligman Martin E.Causal explanations as a risk factor for depression: Theory and evidence.Psychological Review. 1984;91 (3): 347-74
38. Ranganath Rajesh,Jurafsky Dan,McFarland Dan.It’s not you, it’s me: Detecting flirting and its misperception in speed-dates.Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing; 2009; 2009. 334.
39. Sag Ivan A.,Baldwin Timothy,Bond Francis,Copestake Ann,Flickinger Dan.Multiword expressions: A pain in the neck for NLP.Proceedings from 5th International Conference on Computational Linguistics and Intelligent Text Processing; 2002; 2002. 1.
40. Schwartz H. Andrew,Eichstaedt Johannes C.,Kern Margaret L.,Dziurzynski Lukasz,Agrawal Megha,Park Gregory J.,Lakshmikanth Shrinidhi K.,Jha Sneha,Seligman Martin E. P.,Ungar Lyle H.Characterizing geographic variation in well-being using tweets.Paper presented at Seventh International AAAI Conference on Weblogs and Social Media (ICWSM 2013); 2013; 2013.
41. Schwartz H. Andrew,Eichstaedt Johannes C.,Kern Margaret L.,Dziurzynski Lukasz,Ramones Stephanie M.,Agrawal Megha,Shah Achal,Kosinski Michal,Stillwell David,Seligman Martin E. P.,Ungar Lyle H.Personality, gender, and age in the language of social media: The open-vocabulary approach.PloS One. 2013;8 (9): e73791
42. Stone Philip J.,Dunphy Dexter C.,Smith Marshall S.The general inquirer: A computer approach to content analysis. Cambridge, MA: MIT Press; 1966:
43. Sumner Chris,Byers Alison,Boochever Rachel,Park Gregory J.Predicting dark triad personality traits from Twitter usage and a linguistic analysis of tweets.Proceedings of the Eleventh International Conference on Machine Learning and Applications (ICMLA); 2012; 2012. 386.
44. Taboada Maite,Brooke Julian,Tofiloski Milan,Voll Kimberly,Stede Manfred.Lexicon-based methods for sentiment analysis.Computational Linguistics. 2011;37 (2): 267-307
45. Walther Joseph B.Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition.Computers in Human Behavior. 2007;23 (5): 2538-57
46. Weber Ingmar,Garimella Venkata R. Kiran,Batayneh Alaa.Secular vs. Islamist polarization in Egypt on Twitter.Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining; 2013; 2013. 290.
47. Woodward Julian L.Quantitative newspaper analysis as a technique of opinion research.Social Forces. 1934;12 (4): 526-37
48. Yang Shuang-Hong,White Ryen W.,Horvitz Eric.Pursuing insights about healthcare utilization via geocoded search queries.Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval; 2013; 2013. 993.