Beyond Self-Reports: Using Eye Tracking to Measure Topic and Style Differences in Attention to Social Media Content

References

• Anderson, M. (2015). More Americans are using social media to connect with politicians. Pew Research Center. Retrieved from http://www.pewresearch.org/fact-tank/2015/05/19/more-americans-are-using-social-media-to-connect-with-politicians/
   Google Scholar
• Bakshy, E., Messing, S., & Adamic, L. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132.
   PubMed Web of Science ®Google Scholar
• Barthel, M., Shearer, E., Gottfried, J., & Mitchell, A. (2015). The evolving role of news on Twitter and Facebook. Pew Research Center. Retrieved from http://www.journalism.org/2015/07/14/the-evolving-role-of-news-on-twitter-and-facebook/
   Google Scholar
• Bode, L. (2012). Facebooking it to the polls: A study in online social networking and political behavior. Journal of Information Technology & Politics, 9(4), 352–369. doi:10.1080/19331681.2012.709045
   Google Scholar
• Bode, L. (2015). Political news in the news feed: Learning politics from social media. Mass Communication and Society, 19(1), 24–48. doi:10.1080/15205436.2015.1045149
   Web of Science ®Google Scholar
• Bode, L., Vraga, E. K., Borah, P., & Shah, D. V. (2014). A new space for political behavior: Political social networking and its democratic consequences. Journal of Computer-Mediated Communication, 19(3), 414–429. doi:10.1111/jcc4.12048
   Web of Science ®Google Scholar
• Bradburn, N. M., Rips, L., & Shevell, S. (1987). Answering autobiographical questions: The impact of memory and inference on surveys. Science, 236, 157–161. doi:10.1126/science.3563494
   PubMed Web of Science ®Google Scholar
• Bryant, J., Thompson, S., & Finklea, B. (2012). Fundamentals of media effects (2nd ed.). Waveland Press, Inc. Long Grove, IL: Waveland Press.
   Google Scholar
• Burke, M., Marlow, C., & Lento, T. (2010, April). Social network activity and social well-being. CHI ’10: Proceedings of the SIGCHI Conference on Human Factors in Social Computing, pp. 1909–1912. Atlanta, GA.
   Google Scholar
• Buschman, T. J., & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 315(5820), 1860–1862. doi:10.1126/science.1138071
   PubMed Web of Science ®Google Scholar
• Cho, J., Shah, D. V., McLeod, J. M., McLeod, D. M., Scholl, R. M., & Gotlieb, M. R. (2009). Campaigns, reflection, and deliberation: Advancing an O-S-R-O-R model of communication effects. Communication Theory, 19, 66–88. doi:10.1111/comt.2009.19.issue-1
   Web of Science ®Google Scholar
• Constine, J. (2014). American users spend an average of 40 minutes per day on Facebook. TechCrunch. Retrieved from http://techcrunch.com/2014/07/23/facebook-usage-time/
   Google Scholar
• Cooper, B. B. (2013). 7 Powerful Facebook statistics you should know about. Fast Company. Retrieved from http://www.fastcompany.com/3022301/work-smart/7-powerful-facebook-statistics-you-should-know-about
   Google Scholar
• Duchowski, A. (2007). Eye tracking methodology: Theory and practice (Vol. 373). London, UK: Springer Science & Business Media.
   Google Scholar
• Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12, 1143–1168. doi:10.1111/jcmc.2007.12.issue-4
   Web of Science ®Google Scholar
• Ellison, N. B., Steinfield, C., & Lampe, C. (2011). Connection strategies: Social capital implications of Facebook-enabled communication practices. New Media & Society, 13(6), 873–892. doi:10.1177/1461444810385389
   Web of Science ®Google Scholar
• Eveland, W. P., Jr., & Dunwoody, S. (2001). User control and structural isomorphism or disorientation and cognitive load?: Learning from the web versus print. Communication Research, 28(1), 48–78. doi:10.1177/009365001028001002
   Web of Science ®Google Scholar
• Eveland, W. P., Jr., Marton, K., & Seo, M. (2004). Moving beyond ‘just the facts’: The influence of online news on the content and structure of public affairs knowledge. Communication Research, 31, 82–108. doi:10.1177/0093650203260203
   Web of Science ®Google Scholar
• Facebook. (2015). Stats. Retrieved from http://newsroom.fb.com/company-info/
   Google Scholar
• Frey, L. R., Botan, C. H., & Kreps, G. L. (2000). Investigating Communication (2nd ed.). Boston, MA: Allyn and Bacon.
   Google Scholar
• Garrett, R. K. (2013). Selective exposure: New methods and new directions. Communication Methods and Measures, 7, 247–256. doi:10.1080/19312458.2013.835796
   Google Scholar
• Gearhart, S., & Zhang, W. (2014). Gay bullying and online opinion expression: Testing spiral of silence in the social media environment. Social Science Computer Review, 32(1), 18–36. doi:10.1177/0894439313504261
   Web of Science ®Google Scholar
• Gidlof, K., Holmberg, N., & Sandberg, H. (2012). The use of eye-tracking and retrospective interviews to study teenagers’ exposure to online advertising. Visual Communication, 11(3), 329–345. doi:10.1177/1470357212446412
   Web of Science ®Google Scholar
• Gil de Zúñiga, H., Jung, N., & Valenzuela, S. (2012). Social media use for news and individuals’ social capital, civic engagement and political participation. Journal of Computer-Mediated Communication, 17(3), 319–336. doi:10.1111/j.1083-6101.2012.01574.x
   Web of Science ®Google Scholar
• Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. Boczkowski, & K. Foot (Ed.), Media Technologies: Essays on Communication, Materiality, and Society (pp. 167–194). Cambridge, MA: MIT Press.
   Google Scholar
• Glenn, N. D., & Grimes, M. (1968). Aging, voting, and political interest. American Sociological Review, 33(4), 563–575. doi:10.2307/2092441
   Web of Science ®Google Scholar
• Glynn, C. J., Huge, M. E., & Hoffman, L. H. (2012). All the news that’s fit to post: A profile of news use on social networking sites. Computers in Human Behavior, 28(1), 113–119. doi:10.1016/j.chb.2011.08.017
   Web of Science ®Google Scholar
• Graham, D. J., Orquin, J. L., & Visschers, V. H. (2012). Eye tracking and nutrition label use: A review of the literature and recommendations for label enhancement. Food Policy, 37(4), 378–382. doi:10.1016/j.foodpol.2012.03.004
   Web of Science ®Google Scholar
• Hermida, A., Fletcher, F., Korell, D., & Logan, D. (2012). Share, like, recommend: Decoding the social media news consumer. Journalism Studies, 13, 815–824. doi:10.1080/1461670X.2012.664430
   Web of Science ®Google Scholar
• Jang, S. M., Lee, H., & Park, Y. J. (2014). The more friends, the less political talk? Predictors of Facebook discussions among college students. Cyberpsychology, Behavior and Social Networking, 17, 271–275. doi:10.1089/cyber.2013.0477
   PubMed Web of Science ®Google Scholar
• Jones, J. M. (2014, March 28). Young Americans’ affinity for democratic party has grown: majority have consistently aligned with democratic party since 2006. Gallup. Retrieved from http://www.gallup.com/poll/168125/young-americans-affinity-democratic-party-grown.aspx
   Google Scholar
• Junco, R. (2012). The relationship between frequency of Facebook use, participation in Facebook activities, and student engagement. Computers & Education, 58, 162–171. doi:10.1016/j.compedu.2011.08.004
   Web of Science ®Google Scholar
• Junco, R. (2013). Comparing actual and self-reported measures of Facebook use. Computers in Human Behavior, 29(3), 626–631. doi:10.1016/j.chb.2012.11.007
   Web of Science ®Google Scholar
• Junco, R., Heibergert, G., & Loken, E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27, 119–132. doi:10.1111/jca.2011.27.issue-2
   Web of Science ®Google Scholar
• Kim, Y. (2011). The contribution of social network sites to exposure to political difference: The relationships among SNSs, online political messaging, and exposure to cross-cutting perspectives. Computers in Human Behavior, 27, 971–977. doi:10.1016/j.chb.2010.12.001
   Web of Science ®Google Scholar
• Klimmt, C., Vorderer, P., & Ritterfeld, U. (2007). Interactivity and generalizability: New media, new challenges. Communication Methods and Measures, 1, 169–179. doi:10.1080/19312450701434961
   Google Scholar
• Kruikemeier, S., van Noort, G., Vliegenthart, R., & de Vreese, C. H. (2013). Getting closer: The effects of personalized and interactive online political communication. European Journal of Communication, 28, 53–66. doi:10.1177/0267323112464837
   Web of Science ®Google Scholar
• Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108, 480–498. doi:10.1037/0033-2909.108.3.480
   PubMed Web of Science ®Google Scholar
• Lang, A. (2006). Using the limited capacity model of motivated mediated message processing to design effective cancer communication messages. Journal of Communication, 56, S57–S80. doi:10.1111/jcom.2006.56.issue-s1
   Web of Science ®Google Scholar
• Leckner, S. (2012). Presentation factors affecting reading behaviour in readers of newspaper media: An eye-tracking perspective. Visual Communication, 11(2), 163–184. doi:10.1177/1470357211434029
   Web of Science ®Google Scholar
• Lenhart, A. (2015). Teens, technology and friendships: Videogames, social media and mobile phones play an integral role in how teens meet and interact with friends. Pew Internet, Science, & Tech. Retrieved from http://www.pewinternet.org/2015/08/06/teens-technology-and-friendships/
   Google Scholar
• Macafee, T. (2013). Some of these things are not like the others: Examining motivations and political predispositions among political Facebook activity. Computers in Human Behavior, 29(6), 2766–2775. doi:10.1016/j.chb.2013.07.019
   Web of Science ®Google Scholar
• Mancas, M. (2009). Relative influence of bottom-up and top-down attention. In L. Paletta & J.K. Tsotsos (Eds.), Attention in cognitive systems (pp. 212–226). Heidelberg, Germany: Springer.
   Google Scholar
• Markus, K. A. (2012). Principles and practice of structural equation modeling by Rex B. Kline. Structural Equation Modeling: A Multidisciplinary Journal, 19, 509–512. doi:10.1080/10705511.2012.687667
   Web of Science ®Google Scholar
• Messing, S., & Westwood, S. J. (2014). Selective exposure in the age of social media: Endorsements trump partisan source affiliation when selecting news online. Communication Research, 41(8), 1042–1063. doi:10.1177/0093650212466406
   Web of Science ®Google Scholar
• Mitchell, A., Gottfried, J., & Matsa, K. E. (2015). How Millennials, Gen Xers and Boomers get political news. Pew Research Center: Journalism and Media. Retrieved from http://www.journalism.org/2015/06/01/millennials-political-news/
   Google Scholar
• Mitchell, A., & Page, D. (2013). The role of news on Facebook: Common yet Incidental. Pew Research Center for the People and the Press. Retrieved from http://www.journalism.org/files/2013/10/facebook_news_10-24-2013.pdf
   Google Scholar
• Muller, M. G., Kappas, A., & Olk, B. (2012). Perceiving press photography: A new integrative model, combining iconology with psychophysiological and eye-tracking methods. Visual Communication, 11(3), 307–328. doi:10.1177/1470357212446410
   Google Scholar
• Nielsen. (2010). Social networks, blogs now account for one in every four and a half minutes online. Retrieved from http://www.nielsen.com/us/en/insights/news/2010/social-media-accounts-for-22-percent-of-time-online.html
   Google Scholar
• Nielsen, R. K., & Schrøder, K. C. (2014). The relative importance of social media for accessing, finding, and engaging with news. Digital Journalism, 1–18. doi:10.1080/21670811.2013.872420
   Google Scholar
• Oeldorf-Hirsch, A., & Sundar, S. S. (2015). Posting, commenting, and tagging: Effects of sharing news stories on Facebook. Computers in Human Behavior, 44, 240–249. doi:10.1016/j.chb.2014.11.024
   Web of Science ®Google Scholar
• Pan, B., Hembrooke, H. A., Gay, G. K., Granka, L. A., Feusner, M. K., & Newman, J. K. (2004, March). The determinants of web page viewing behavior: An eye tracking study. Proceedings of the 2004 symposium on Eye tracking research & applications, ACM, pp. 147–154. San Antonio, TX.
   Google Scholar
• Pariser, E. (2011). The filter bubble: What the internet is hiding from you. New York, NY: Penguin Press.
   Google Scholar
• Pew. (2012). In changing news landscape, even television is vulnerable. Retrieved from http://www.people-press.org/2012/09/27/in-changing-news-landscape-even-television-is-vulnerable/
   Google Scholar
• Prior, M. (2009a). Improving media effects research through better measurement of news exposure. The Journal of Politics, 71, 893–908. doi:10.1017/S0022381609090781
   Web of Science ®Google Scholar
• Prior, M. (2009b). The immensely inflated news audience: Assessing bias in self-reported news exposure. Public Opinion Quarterly, 73, 130–143. doi:10.1093/poq/nfp002
   Web of Science ®Google Scholar
• Raacke, J., & Bonds-Raacke, J. (2008). MySpace and Facebook: Applying the uses and gratifications theory to exploring friend-networking sites. CyberPsychology & Behavior, 11(2), 169–174. doi:10.1089/cpb.2007.0056
   PubMedGoogle Scholar
• Rainie, L., Smith, A., Schlozman, K. L., Brady, H., & Verba, S. (2012). Social media and political engagement. Pew Interent and American Life Project. Retrieved from http://www.pewinternet.org/files/old-media//Files/Reports/2012/PIP_SocialMediaAndPoliticalEngagement_PDF.pdf
   Google Scholar
• Rubin, A. M. (1984). Ritualized and instrumental television viewing. Journal of Communication, 34(3), 67–77. doi:10.1111/jcom.1984.34.issue-3
   Web of Science ®Google Scholar
• Rubin, A. M. (2002). The uses-and-gratifications perspective of media effects. In J. Bryant, & D. Zillmann (Eds.), Media effects: Advances in theory and research (pp. 525–548). Hilsdale, NJ: Erlbaum.
   Google Scholar
• Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication and Society, 3, 3–37. doi:10.1207/S15327825MCS0301_02
   Google Scholar
• Schwarz, N., & Oyserman, D. (2001). Asking questions about behavior: Cognition, communication, and questionnaire construction. American Journal of Evaluation, 22(2), 127–160. doi:10.1177/109821400102200202
   Web of Science ®Google Scholar
• Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y. (2011). Facebook as a toolkit: A uses and gratification approach to unbundling feature use. Computers in Human Behavior, 27, 2322–2329. doi:10.1016/j.chb.2011.07.011
   Web of Science ®Google Scholar
• Staddon, J., Acquisti, A., & LeFevre, K. (2013). Self-reported social network behavior: Accuracy predictors and implications for the privacy paradox. IEEE: Computer Society, 295–302.
   Google Scholar
• Stroud, N. J. (2010). Polarization and partisan selective exposure. Journal of Communication, 60(3), 556–576. doi:10.1111/j.1460-2466.2010.01497.x
   Web of Science ®Google Scholar
• Sundar, S. S., & Limperos, A. M. (2013). Uses and grats 2.0: New gratifications for new media. Journal of Broadcasting & Electronic Media, 57, 504–525. doi:10.1080/08838151.2013.845827
   Web of Science ®Google Scholar
• Taber, C. S., & Lodge, M. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50, 755–769. doi:10.1111/ajps.2006.50.issue-3
   Web of Science ®Google Scholar
• Tewksbury, D. (2003). What do Americans really want to know? Tracking the behavior of news readers on the Internet. Journal of Communication, 53(4), 694–710. doi:10.1111/jcom.2003.53.issue-4
   Web of Science ®Google Scholar
• Tewksbury, D., & Althaus, S. L. (2000). Differences in knowledge acquisition among readers of the paper and online versions of a national newspaper. Journalism & Mass Communication Quarterly, 77, 457–479. doi:10.1177/107769900007700301
   Web of Science ®Google Scholar
• Thorson, K. (2012). What does it mean to be a good citizen? Citizenship vocabularies as resources for action. The ANNALS of the American Academy of Political and Social Science, 644(1), 70–85. doi:10.1177/0002716212453264
   Web of Science ®Google Scholar
• Thorson, K., Vraga, E. K., & Klinger-Vilenchik, N. (2014). Don’t push your opinions on me: Young citizens and political etiquette on Facebook. In J. A. Hendricks, & D. Schill (Eds.), Presidential campaigning and social media: An analysis of the 2012 campaign (pp. 74–93). Boulder, CO: Oxford University Press.
   Google Scholar
• Tourangeau, R., & Rasinski, K. (1988). Cognitive processes underlying context effects in attitude measurement. Psychological Bulletin, 103, 299–314. doi:10.1037/0033-2909.103.3.299
   Web of Science ®Google Scholar
• Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Turcotte, J., York, C., Irving, J., Scholl, R., & Pingree, R. J. (2015). News recommendations from social media opinion leaders: Effects on media trust and information seeking. Journal of Computer-Mediated Communication, 20, 520–535. doi:10.1111/jcc4.12127
   Web of Science ®Google Scholar
• Vitak, J., Zube, P., Smock, A., Carr, C. T., Ellison, N., & Lampe, C. (2011). It’s complicated: Facebook users’ political participation in the 2008 election. Cyberpsychology, Behavior and Social Networking, 14(3), 107–114. doi:10.1089/cyber.2009.0226
   PubMed Web of Science ®Google Scholar
• Vraga, E. K., Bode, L., Smithson, A., & Troller-Renfree, S. (2014). Blurred lines: Defining social, news, and political posts on Facebook. Journal of Information Technology and Politics, advance online publication. doi:10.1080/19331681.2016.1160265
   Google Scholar
• Vraga, E. K., Bode, L., & Troller-Renfree, S. (2015a). Eyes don’t lie: Validating self-reported measures of attention on social media. Paper presented to the Association for Education in Journalism and Mass Communication (Communication Theory & Methodology), San Francisco, CA.
   Google Scholar
• Vraga, E. K., Thorson, K., Kligler-Vilenchik, N., & Gee, E. (2015b). How individual sensitivities to disagreement shape youth political expression on Facebook. Computers in Human Behavior, 45, 281–289. doi:10.1016/j.chb.2014.12.025
   Web of Science ®Google Scholar
• Weber, T. E. (2010). How Facebook decides what to put in your News Feed – These 10 secrets reveal all. Business Insider. Retrieved from http://www.businessinsider.com/how-facebook-decides-what-to-put-in-your-news-feed–these-10-secrets-reveal-all-2010-10
   Google Scholar
• Weber, R., Mangus, M., & Huskey, R. (2015). Brain imaging in communication research: A practical guide to understanding and evaluating fMRI studies. Communication Methods and Measures, 9, 5–29. doi:10.1080/19312458.2014.999754
   Web of Science ®Google Scholar
• Weeks, B. E., & Holbert, R. L. (2013). Predicting dissemination of news content in social media: A focus on reception, friending, and partisanship. Journalism & Mass Communication Quarterly, 90, 212–232. doi:10.1177/1077699013482906
   Web of Science ®Google Scholar
• Wise, K., Bolls, P. D., & Schaefer, S. R. (2008). Choosing and reading online news: How available choice affects cognitive processing. Journal of Broadcasting & Electronic Media, 52, 69–85. doi:10.1080/08838150701820858
   Web of Science ®Google Scholar
• Zaller, J. (1992). The nature and origins of mass opinion. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Zillmann, D. (1999). Exemplification theory: Judging the whole by some of its parts. Media Psychology, 1, 69–94. doi:10.1207/s1532785xmep0101_5
   Google Scholar
• Zillmann, D. (2006). Exemplification effects in the promotion of safety and health. Journal of Communication, 56, S221–S237. doi:10.1111/jcom.2006.56.issue-s1
   Web of Science ®Google Scholar