Social Media Analyses for Social Measurement.

Demonstrations that analyses of social media content can align with measurement from sample surveys have raised the question of whether survey research can be supplemented or even replaced with less costly and burdensome data mining of already-existing or "found" social media content. But just how trustworthy such measurement can be-say, to replace official statistics-is unknown. Survey researchers and data scientists approach key questions from starting assumptions and analytic traditions that differ on, for example, the need for representative samples drawn from frames that fully cover the population. New conversations between these scholarly communities are needed to understand the potential points of alignment and non-alignment. Across these approaches, there are major differences in (a) how participants (survey respondents and social media posters) understand the activity they are engaged in; (b) the nature of the data produced by survey responses and social media posts, and the inferences that are legitimate given the data; and (c) practical and ethical considerations surrounding the use of the data. Estimates are likely to align to differing degrees depending on the research topic and the populations under consideration, the particular features of the surveys and social media sites involved, and the analytic techniques for extracting opinions and experiences from social media. Traditional population coverage may not be required for social media content to effectively predict social phenomena to the extent that social media content distills or summarizes broader conversations that are also measured by surveys.

[1]  Frederick G. Conrad,et al.  Comparisons of Online Recruitment Strategies for Convenience Samples , 2016 .

[2]  Josh Pasek,et al.  When will Nonprobability Surveys Mirror Probability Surveys? Considering Types of Inference and Weighting Strategies as Criteria for Correspondence , 2016 .

[3]  Cliff Lampe,et al.  Big Data in Survey Research AAPOR Task Force Report , 2015 .

[4]  Nora A Draper,et al.  The Tradeoff Fallacy: How Marketers are Misrepresenting American Consumers and Opening Them Up to Exploitation , 2015 .

[5]  Thomas R. Ioerger,et al.  Precision and Disclosure in Text and Voice Interviews on Smartphones , 2015, PloS one.

[6]  Lada A. Adamic,et al.  Exposure to ideologically diverse news and opinion on Facebook , 2015, Science.

[7]  S. Mo Jang,et al.  Assessing the Carrying Capacity of Twitter and Online News , 2015 .

[8]  Munmun De Choudhury,et al.  Identity Management and Mental Health Discourse in Social Media , 2015, WWW.

[9]  James Grimmelmann,et al.  The Law and Ethics of Experiments on Social Media Users , 2015 .

[10]  Georgios Paltoglou,et al.  Signals of Public Opinion in Online Communication , 2015 .

[11]  Reza Zafarani,et al.  Sarcasm Detection on Twitter: A Behavioral Modeling Approach , 2015, WSDM.

[12]  Michael W. Link,et al.  Social Media in Public Opinion Research Executive Summary of the Aapor Task Force on Emerging Technologies in Public Opinion Research , 2014 .

[13]  G. Tellis,et al.  Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation , 2014 .

[14]  Jeffrey T. Hancock,et al.  Experimental evidence of massive-scale emotional contagion through social networks , 2014, Proceedings of the National Academy of Sciences.

[15]  Michael Gamon,et al.  Online And Social Media Data As A Flawed Continuous Panel Survey , 2014 .

[16]  Mario Callegaro,et al.  Mobile technologies for conducting, augmenting and potentially replacing surveys , 2014 .

[17]  Vasile Rus,et al.  A Machine Learning Approach to Pronominal Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems , 2014, CICLing.

[18]  Jon-Kar Zubieta,et al.  Real-Time Sharing and Expression of Migraine Headache Suffering on Twitter: A Cross-Sectional Infodemiology Study , 2014, Journal of medical Internet research.

[19]  W. R. Neuman,et al.  The Dynamics of Public Attention: Agenda‐Setting Theory Meets Big Data , 2014 .

[20]  Zeynep Tufekci,et al.  Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls , 2014, ICWSM.

[21]  D. Lazer,et al.  The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.

[22]  Arthur C. Graesser,et al.  Automated Evaluation of Text and Discourse with Coh-Metrix: List of Tables , 2014 .

[23]  Giuseppe Porro,et al.  Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens’ political preferences with an application to Italy and France , 2013, New Media Soc..

[24]  Michael J. Cafarella,et al.  Using Social Media to Measure Labor Market Flows , 2014 .

[25]  Andreas Graefe,et al.  Accuracy of Vote Expectation Surveys in Forecasting Elections , 2014 .

[26]  M. Couper Is the sky falling? new technology, changing media, and the future of surveys , 2013 .

[27]  M. Couper,et al.  How well do volunteer web panel surveys measure sensitive behaviours in the general population, and can they be improved? A comparison with the third British National Survey of Sexual Attitudes & Lifestyles (Natsal-3) , 2013, The Lancet.

[28]  Mark Edward Huberty,et al.  Multi-cycle forecasting of congressional elections with social media , 2013, PLEAD '13.

[29]  Annice E Kim,et al.  Can Tweets Replace Polls? A U.S. Health‐Care Reform Case Study , 2013 .

[30]  The Future of Social Media, Sociality, and Survey Research , 2013 .

[31]  Joseph Murphy,et al.  Social Media, Sociality, and Survey Research , 2013 .

[32]  King-wa Fu,et al.  Analyzing Online Sentiment to Predict Telephone Poll Results , 2013, Cyberpsychology Behav. Soc. Netw..

[33]  Toby Hopp,et al.  Is Ghost Blogging Like Speechwriting? A Survey of Practitioners About the Ethics of Ghost Blogging , 2013 .

[34]  Kenneth Prewitt,et al.  The 2012 Morris Hansen Lecture: Thank You Morris, et al., For Westat, et al. , 2013 .

[35]  Ruben Castro,et al.  Inconsistent Respondents and Sensitive Questions , 2013 .

[36]  Jill Burstein,et al.  Handbook of Automated Essay Evaluation Current Applications and New Directions , 2018 .

[37]  Tom W. Smith,et al.  Survey-Research Paradigms Old and New , 2013 .

[38]  Michael J. Jensen,et al.  Psephological investigations: Tweets, votes, and unknown unknowns in the republican nomination process , 2013 .

[39]  Roger Tourangeau,et al.  Summary Report of the AAPOR Task Force on Non-probability Sampling , 2013 .

[40]  Ludwig Fahrmeir,et al.  Regression: Models, Methods and Applications , 2013 .

[41]  Viktor Mayer-Schnberger,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2013 .

[42]  Declan Butler,et al.  When Google got flu wrong , 2013, Nature.

[43]  J. Brick,et al.  Explaining Rising Nonresponse Rates in Cross-Sectional Surveys , 2013 .

[44]  Frauke Kreuter,et al.  Facing the Nonresponse Challenge , 2013 .

[45]  Spiro Kiousis,et al.  Political Public Relations : Old Practice, New Theory-Building , 2013 .

[46]  R. Tourangeau,et al.  Introduction New Challenges to Social Measurement , 2013 .

[47]  D. Boyd,et al.  Sociality Through Social Network Sites , 2013 .

[48]  Antal van den Bosch,et al.  Relating Political Party Mentions on Twitter with Polls and Election Results , 2013, DIR.

[49]  Daniel Gayo-Avello,et al.  No, You Cannot Predict Elections with Twitter , 2012, IEEE Internet Comput..

[50]  Scott Keeter,et al.  Presidential Address: Survey Research, Its New Frontiers, and Democracy , 2012 .

[51]  Nello Cristianini,et al.  Nowcasting Events from the Social Web with Statistical Learning , 2012, TIST.

[52]  Shrikanth S. Narayanan,et al.  A System for Real-time Twitter Sentiment Analysis of 2012 U.S. Presidential Election Cycle , 2012, ACL.

[53]  D. Boyd,et al.  CRITICAL QUESTIONS FOR BIG DATA , 2012 .

[54]  Lindsay T. Graham,et al.  A Review of Facebook Research in the Social Sciences , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.

[55]  Johan Bos,et al.  Predicting the 2011 Dutch Senate Election Results with Twitter , 2012 .

[56]  R. Groves Three Eras of Survey Research , 2011 .

[57]  Scott A. Golder,et al.  Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures , 2011 .

[58]  C. Fuchs,et al.  Internet and Surveillance: The Challenges of Web 2.0 and Social Media , 2011 .

[59]  J. Wolfers,et al.  Forecasting Elections: Voter Intentions Versus Expectations , 2011 .

[60]  Matthew Mohebbi,et al.  Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) Pandemic , 2011, PloS one.

[61]  Leonard Reinecke,et al.  Privacy Online - Perspectives on Privacy and Self-Disclosure in the Social Web , 2011 .

[62]  Panagiotis Takis Metaxas,et al.  Limits of Electoral Predictions Using Twitter , 2011, ICWSM.

[63]  S. Presser,et al.  The growth of survey research in the United States: Government-sponsored surveys, 1984–2004 , 2011 .

[64]  Ben O'Loughlin,et al.  TRUST, CONFIDENCE, AND CREDIBILITY , 2011 .

[65]  Alice E. Marwick,et al.  To See and Be Seen: Celebrity Practice on Twitter , 2011 .

[66]  Duncan J. Watts,et al.  Who says what to whom on twitter , 2011, WWW.

[67]  Debra Lauterbach,et al.  It's not that i don't have problems, i'm just not putting them on facebook: challenges and opportunities in using online social networks for health , 2011, CSCW.

[68]  Danah Boyd,et al.  I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience , 2011, New Media Soc..

[69]  M. F. Schober,et al.  Self-Deceptive Speech: A Psycholinguistic View , 2011 .

[70]  Cliff Lampe,et al.  Negotiating Privacy Concerns and Social Capital Needs in a Social Media Environment , 2011, Privacy Online.

[71]  Charu C. Aggarwal,et al.  An Introduction to Social Network Data Analytics , 2011, Social Network Data Analytics.

[72]  M. Zimmer “But the data is already public”: on the ethics of research in Facebook , 2010, Ethics and Information Technology.

[73]  K. Selçuk Candan,et al.  How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media? , 2010, ICWSM.

[74]  Lauren B Solberg Data Mining on Facebook: A Free Space for Researchers or an IRB Nightmare? , 2010 .

[75]  Dietrich Klakow,et al.  A survey on the role of negation in sentiment analysis , 2010, NeSp-NLP@ACL.

[76]  Sasha Blair-Goldensohn,et al.  The viability of web-derived polarity lexicons , 2010, NAACL.

[77]  Eric Gilbert,et al.  Widespread Worry and the Stock Market , 2010, ICWSM.

[78]  Isabell M. Welpe,et al.  Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment , 2010, ICWSM.

[79]  Brendan T. O'Connor,et al.  From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series , 2010, ICWSM.

[80]  Alcides Velasquez,et al.  Motivations to participate in online communities , 2010, CHI.

[81]  Bernardo A. Huberman,et al.  Predicting the Future with Social Media , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[82]  Robert M. Groves,et al.  Total Survey Error: Past, Present, and Future , 2010 .

[83]  Helen Nissenbaum,et al.  Privacy in Context - Technology, Policy, and the Integrity of Social Life , 2009 .

[84]  Anwar M. Ghuloum,et al.  ViewpointFace the inevitable, embrace parallelism , 2009, CACM.

[85]  Adam Jacobs,et al.  The pathologies of big data , 2009, Commun. ACM.

[86]  Roger Tourangeau,et al.  Taking the Audio Out of Audio-CASI , 2009 .

[87]  Sunghee Lee,et al.  Estimation for Volunteer Panel Web Surveys Using Propensity Score Adjustment and Calibration Adjustment , 2009 .

[88]  M. Mathews,et al.  An Interview with , 2009 .

[89]  Olli Pitkänen,et al.  Users' Awareness of Privacy on Online Social Networking Sites - Case Facebook , 2009, Bled eConference.

[90]  F. Kreuter,et al.  Social Desirability Bias in CATI, IVR, and Web Surveys The Effects of Mode and Question Sensitivity , 2008 .

[91]  Mick P. Couper,et al.  Designing Effective Web Surveys , 2008 .

[92]  A. Peytchev An Interview with Kenneth Prewitt , 2008 .

[93]  G. Loosveldt,et al.  An evaluation of the weighting procedures for an online access panel survey , 2008 .

[94]  Saroj Kaushik,et al.  Automatic Text Summarization , 2008 .

[95]  D. Watts,et al.  Influentials, Networks, and Public Opinion Formation , 2007 .

[96]  R. Tourangeau,et al.  Sensitive questions in surveys. , 2007, Psychological bulletin.

[97]  Paul Resnick,et al.  Follow the reader: filtering comments on slashdot , 2007, CHI.

[98]  David J. Leinweber,et al.  Stupid Data Miner Tricks , 2007 .

[99]  Roger Burrows,et al.  The Coming Crisis of Empirical Sociology , 2007, Sociology.

[100]  Michael A. Dimock,et al.  Gauging the Impact of Growing Nonresponse on Estimates from a National RDD Telephone Survey , 2006 .

[101]  R. Groves Nonresponse Rates and Nonresponse Bias in Household Surveys , 2006 .

[102]  Janyce Wiebe,et al.  Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2005, HLT.

[103]  H. Weisberg The Total Survey Error Approach: A Guide to the New Science of Survey Research , 2005 .

[104]  Alastair J. Gill,et al.  Language With Character: A Stratified Corpus Comparison of Individual Differences in E-Mail Communication , 2006 .

[105]  P. Biemer,et al.  Introduction to Survey Quality , 2003 .

[106]  B. Schwartz,et al.  Maximizing versus satisficing: happiness is a matter of choice , 2002 .

[107]  S. M. Rogers,et al.  Adolescent sexual behavior, drug use, and violence: increased reporting with computer survey technology. , 1998, Science.

[108]  K. Murphy,et al.  Statistical Power Analysis: A Simple and General Model for Traditional and Modern Hypothesis Tests, Second Ediction , 1998 .

[109]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[110]  Tom W. Smith,et al.  ASKING SENSITIVE QUESTIONS THE IMPACT OF DATA COLLECTION MODE, QUESTION FORMAT, AND QUESTION CONTEXT , 1996 .

[111]  Wendy E. Mackay,et al.  Triggers and barriers to customizing software , 1991, CHI.

[112]  R. Rosenthal The file drawer problem and tolerance for null results , 1979 .