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Editorial

Editorial of the Special Issue on Following User Pathways: Key Contributions and Future Directions in Cross-Platform Social Media Research

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References

  • Abel, F., Gao, Q., Houben, G.-J., & Tao, K. (2011). Semantic enrichment of Twitter posts for user profile construction on the social web. In G. Antoniou, M. Grobelnik, E. Simperl, B. Parsia, D. Plexousakis, P. De Leenheer, & J. Pan ( Hrsg.), Proceedings of the 8th Extended Semantic Web Conference (pp. 375–389). Berlin, Germany: Springer Berlin/Heidelberg.
  • Aral, S., Dellarocas, C., & Godes, D. (2013). Introduction to the special issue—Social media and business transformation: A framework for research. Information Systems Research, 24(1), 3–13. doi:10.1287/isre.1120.0470
  • Azizian, S., Rastegari, E., Ricks, B., & Hall, M. (2017). Identifying personal messages: a step towards product/service review and opinion mining. In International Conference on Computational Science and Computational Intelligence.
  • Backstrom, L., Dwork, C., & Kleinberg, J. (2007). Wherefore art thou r3579x? Anonymized social networks, hidden patterns, and structural steganography. Proceedings of the 16th International Conference on World Wide Web - WWW ’07, 54(12), 181. doi:http://doi.org/10.1145/1242572.1242598
  • Baker, P. M., Bricout, J. C., Moon, N. W., Coughlan, B., & Pater, J. (2013). Communities of participation: A comparison of disability and aging identified groups on Facebook and LinkedIn. Telematics and Informatics, 30(1), 22–34. doi:10.1016/j.tele.2012.03.004
  • Baldwin, T., Cook, P., Lui, M., MacKinlay, A., & Wang, L. (2013, October). How noisy social media text, how different social media sources? In IJCNLP (pp. 356–364). Nagoya, Japan.
  • Balmas, M. (2014). When fake news becomes real: Combined exposure to multiple news sources and political attitudes of inefficacy, alienation, and cynicism. Communication Research, 41(3), 430–454. doi:10.1177/0093650212453600
  • Bamman, D., O'Connor, B., & Smith, N. (2012). Censorship and deletion practices in Chinese social media. First Monday, 17, 3.
  • Becker, H., Naaman, M., & Gravano, L., 2010, February. Learning similarity metrics for event identification in social media. In Proceedings of the third ACM international conference on Web search and data mining (pp. 291–300). ACM.
  • Berners-Lee, T. (2010). Long live the web. Scientific American, 303(6), 80–85. doi:10.1038/scientificamerican1210-80
  • Bessi, A., Zollo, F., Del Vicario, M., Puliga, M., Scala, A., Caldarelli, G., … Preis, T. (2016). Users polarization on Facebook and YouTube. PloS One, 11(8), e0159641. doi:10.1371/journal.pone.0159641
  • Bloom, R., Amber, K. T., Hu, S., & Kirsner, R. (2015). Google search trends and skin cancer: Evaluating the US population’s interest in skin cancer and its association with melanoma outcomes. JAMA Dermatology, 151(8), 903–905. doi:10.1001/jamadermatol.2015.12
  • Bolton, R. N., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayi, S., Gruber, T., … Solnet, D. (2013). Understanding generation Y and their use of social media: A review and research agenda. Journal of Service Management, 24(3), 245–267. doi:10.1108/09564231311326987
  • boyd, d., & Crawford, K. (2011, September 21). Six provocations for big data. In A decade in internet time: Symposium on the dynamics of the internet and society (Vol. 21). Oxford: Oxford Internet Institute.
  • Burnap, P., Rana, O., Williams, M., Housley, W., Edwards, A., Morgan, J., … Conejero, J. (2015). COSMOS: Towards an integrated and scalable service for analysing social media on demand. International Journal of Parallel, Emergent and Distributed Systems, 30(2), 80–100. http://doi.org/10.1080/17445760.2014.902057
  • Caton, S., Dukat, C., Grenz, T., Haas, C., Pfadenhauer, M., & Weinhardt, C., 2012, November. Foundations of trust: Contextualising trust in social clouds. In Cloud and Green Computing (CGC), 2012 Second International Conference on (pp. 424–429). IEEE.
  • Caton, S., Hall, M., & Weinhardt, C. (2015). How do politicians use Facebook? An applied social observatory. Big Data & Society, 2(2), 2053951715612822. doi:10.1177/2053951715612822
  • Chorley, M. J., Colombo, G. B., Allen, S. M., & Whitaker, R. M. (2012). Better the Tweeter you know: Social signals on Twitter. In 2012 ASE/IEEE international conference on social computing (pp. 277–282). Amsterdam, The Netherlands: ASE/IEEE International Conference on Social Computing. doi:http://doi.org/10.1109/SocialCom-PASSAT.2012.27
  • Chorley, M. J., Whitaker, R. M., & Allen, S. M. (2015). Personality and location-based social networks. Computers in Human Behavior, 46, 45–56. doi:10.1016/j.chb.2014.12.038
  • Chorley, M. J., & Williams, M. J. (2017). Foursquare. In L. Sloan & A. Quan-Haase (Eds.), The SAGE handbook of social media research methods (pp. 610–626). London, UK: SAGE.
  • Chung, J., & Mustafaraj, E. (2011). Can collective sentiment expressed on twitter predict political elections? In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (pp. 1770–1771). San Francisco, CA. https://doi.org/10.1007/s00247-002-0848-7
  • Cioffi-Revilla, C. (2010). Computational social science. Wiley Interdisciplinary Reviews: Computational Statistics, 2(3), 259–271. doi:https://doi.org/10.1002/wics.95
  • Corley, C. D., Cook, D. J., Mikler, A. R., & Singh, K. P. (2010). Text and structural data mining of influenza mentions in web and social media. International Journal of Environmental Research and Public Health, 7(2), 596–615. doi:10.3390/ijerph7020596
  • Correa, T., Hinsley, A. W., & De Zuniga, H. G. (2010). Who interacts on the Web?: The intersection of users’ personality and social media use. Computers in Human Behavior, 26(2), 247–253. doi:10.1016/j.chb.2009.09.003
  • Cranshaw, J., Hong, J. I., & Sadeh, N. (2012). The livehoods project: utilizing social media to understand the dynamics of a city. Icwsm (pp. 58–65). Dublin.
  • Culotta, A., 2014. Reducing sampling bias in social media data for county health inference. In Joint Statistical Meetings Proceedings (pp. 1–12).
  • Davenport, S. W., Bergman, S. M., Bergman, J. Z., & Fearrington, M. E. (2014). Twitter versus Facebook: Exploring the role of narcissism in the motives and usage of different social media platforms. Computers in Human Behavior, 32, 212–220. doi:10.1016/j.chb.2013.12.011
  • De Choudhury, M., Lin, Y. R., Sundaram, H., Candan, K. S., Xie, L., & Kelliher, A. (2010). How does the data sampling strategy impact the discovery of information diffusion in social media? ICWSM, 10, 34–41.
  • Duggan, M., & Brenner, J. (2013). The demographics of social media users, 2012 (Vol. 14). Washington, DC: Pew Research Center’s Internet & American Life Project.
  • 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(4), 1143–1168. doi:10.1111/jcmc.2007.12.issue-4
  • Ewig, C. (2011). Social Media: Theorie und praxis digitaler sozialität/social media: Theory and practice of digital sociality. In Social media: theorie und praxis digitaler sozialität. Frankfurt, Germany: Peter Lang.
  • Eysenbach, G., & Till, J. E. (2001). Ethical issues in qualitative research on internet communities. British Medical Journal, 323, 1103–1105. https://doi.org/10.1136/bmj.323.7321.1103
  • Felt, A., & Evans, D. (2008). Privacy protection for social networking APIs. Security, (Section 4) 34, Retrieved from http://www.cs.virginia.edu/felt/privacybyproxy.pdf
  • Frikken, K. B., & Golle, P. (2006). Private social network analysis: How to assemble pieces of a graph privately. WPES, 89–98. doi:http://doi.org/10.1145/1179601.1179619
  • Garaizar, P., & Reips, U.-D. (2014). Build your own social network laboratory with social lab: A tool for research in social media. Behavior Research Methods, 46(2), 430–438. doi:10.3758/s13428-013-0385-3
  • Gayo-Avello, D. (2011). Don’t turn social media into another ‘Literary Digest’ poll. Communications of the ACM, 54(10), 121–128. doi:10.1145/2001269
  • Giglietto, F., Rossi, L., & Bennato, D. (2012). The open laboratory: limits and possibilities of using Facebook, Twitter, and YouTube as a research data source. Journal of Technology in Human Services, 30(3–4), 145–159.
  • Gilbert, E., & Karahalios, K. (2009, April). Predicting tie strength with social media. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 211–220). New York, NY: ACM.
  • González-Bailón, S., Wang, N., Rivero, A., Borge-Holthoefer, J., & Moreno, Y. (2014). Assessing the bias in samples of large online networks. Social Networks, 38, 16–27. doi:10.1016/j.socnet.2014.01.004
  • Gosling, S. D., & Mason, W. (2015). Internet research in psychology. Annual Review of Psychology, 66(1), 877–902. doi:10.1146/annurev-psych-010814-015321
  • Grange, C. (2018). The generativity of social media: Opportunities, challenges, and guidelines for conducting experimental research. International Journal of Human-Computer Interaction. doi:https://doi.org/10.1207/s15327590ijhc2003
  • Grimmelmann, J. (2015). The law and ethics of experiments on social media users. Colorado Technology Law Journal, 13(219), 219–272. Retrieved from http://ssrn.com/abstract=2604168
  • Gruzd, A. (2016). Who are we modelling: Bots or humans? In Proceedings of the 25th international conference companion on world wide web (pp. 551). New York, NY, USA: International World Wide Web Conferences Steering Committee.
  • Gudelunas, D. (2012). There’s an app for that: The uses and gratifications of online social networks for gay men. Sexuality & Culture, 16(4), 347–365. doi:10.1007/s12119-012-9127-4
  • Hall, M. (2018). A mixed-methods approach to ethical data extraction in social media studies. London, UK: SAGE Research Methods Case Study.
  • Hall, M., & Caton, S. (2017). Am I who I say I am? Unobtrusive self-representation and personality recognition on Facebook. PloS One, 12(9), e0184417. doi:10.1371/journal.pone.0184417
  • Hall, M., Mazarakis, A., Peters, I., Chorley, M., Caton, S., Mai, J.-E., & Strohmaier, M. (2016). Following user pathways: Cross platform and mixed methods analysis. Proceedings of the 2016 CHI conference extended abstracts on human factors in computing systems (pp. 3400–3407). San Jose, USA: ACM Press. https://doi.org/http://dx.doi.org/10.1145/2851581.2856500
  • Hanson, G., Haridakis, P. M., Cunningham, A. W., Sharma, R., & Ponder, J. D. (2010). The 2008 Presidential campaign: Political cynicism in the age of Facebook, Myspace, and YouTube. Mass Communication and Society, 13(5), 584–607. doi:10.1080/15205436.2010.5134
  • Hay, M., Miklau, G., Jensen, D., Towsley, D., & Li, C. (2010). Resisting structural re-identification in anonymized social networks. The VLDB Journal—The International Journal on Very Large Data Bases, 19(6), 797–823.
  • Hobbs, W., Friedland, L., Joseph, K., Tsur, O., Wojcik, S., & Lazer, D. (2017). Voters of the Year. 19 Voters Who Were Unintentional Election Poll Sensors on Twitter (ICWSM), 544–547.
  • Hristova, D., Williams, M. J., & Panzarasa, P. (2016). Measuring urban social diversity using interconnected geo-social networks. WWW, 21–30. doi:http://doi.org/10.1145/2872427.2883065
  • Hughes, A. L., & Palen, L. (2014). Social media and emergency management. In J. E. Trainor & T. Subbio (Eds.), Critical issues in disaster science and management: A dialogue between scientists and emergency managers (pp. 349–392). Washington, DC: FEMA Higher Education Project.
  • Hughes, D. J., Rowe, M., Batey, M., & Lee, A. (2012). A tale of two sites: Twitter vs. Facebook and the Personality Predictors of Social Media Usage. Computers in Human Behavior, 28(2), 561–569.
  • Jiang, S. (2017). The role of social media use in improving cancer survivors’ emotional well-being: A moderated mediation study. Journal of Cancer Survivorship, 11(3), 386–392. doi:10.1007/s11764-017-0595-2
  • Jordan, K. (2018). Validity, reliability and the case for participant-centred research: Reflections on a multi-platform social media study. International Journal of Human Computer Interaction.
  • Kazanidis, I., Pellas, N., Fotaris, P., & Tsinakos, A. (2018). Facebook and Moodle integration into instructional media design courses: A comparative analysis of students’ learning experiences using the Community of Inquiry. International Journal of Human-Computer Interaction.
  • Kim, D., Kim, J. H., & Nam, Y. (2014). How does industry use social networking sites? An analysis of corporate dialogic uses of Facebook, Twitter, YouTube, and LinkedIn by industry type. Quality & Quantity, 48(5), 2605–2614. doi:10.1007/s11135-013-9910-9
  • Kivelä, A., & Lyytinen, O. (2004). Topic map aided publishing – A case study of assembly media archive. In STeP 2004 - The 11th Finnish Artificial Intelligence Conference Proceedings. Vantaa, Finland.
  • Koster, M. (1995). Robots in the Web: Threat or treat? OII Spectrum, 2(9), 8–18.
  • Kramer, A. D., Guillory, J. E., & Hancock, J. T., 2014. Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences, 111( 24), pp.8788–8790.
  • Krosnick, J. A. (1999). Survey research. Annual Review of Psychology, 50(1), 537–567. doi:10.1146/annurev.psych.50.1.537
  • Kwak, H., Lee, C., Park, H., & Moon, S., 2010, April. What is Twitter, a social network or a news media? In Proceedings of the 19th international conference on world wide web (pp. 591–600). ACM.
  • Lazer, D., Baum, M., Grinberg, N., Friedland, L., Joseph, K., Hobbs, W., … Watts, D. (2017). Combating fake news: An agenda for research and action drawn from presentations by (May), 1–17. Retrieved from https://shorensteincenter.org/wp-content/uploads/2017/05/Combating-Fake-News-Agenda-for-Research-1.pdf
  • Lazer, D., Brewer, D., Christakis, N., Fowler, J., & King, G. (2009). Life in the network: The coming age of computational social. Science, 323(5915), 721–723.https://doi.org/10.1126/science.1167742.Life
  • Lee, K., Ganti, R., Srivatsa, M., & Liu, L. (2014). When Twitter meets Foursquare: Tweet location prediction using Foursquare. Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 198–207. http://doi.org/10.4108/icst.mobiquitous.2014.258092
  • Lemke, S., Mazarakis, A., & Peters, I. (2015). Understanding scientific conference tweets. In Proceedings of the 17th General Online Research Conference (GOR 2015) (pp. 52–53). Cologne, Germany: German Society for Online Research (DGOF).
  • Lerman, K., & Ghosh, R. (2010). Information contagion: An empirical study of the spread of news on Digg and Twitter social networks. ICWSM, 10, 90–97.
  • Li, Z., & Duan, J. A. (2014). Dynamic strategies for successful online crowdfunding. SSRN Electronic Journal (September). doi:https://doi.org/10.2139/ssrn.2506352
  • Lim, B. H., Lu, D., Chen, T., & Kan, M. Y. (2015). #mytweet via Instagram: Exploring user behaviour across multiple social networks. In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 113–120).
  • Lin, H., & Qiu, L. (2013). Two sites, two voices: Linguistic differences between Facebook status updates and tweets. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8024(LNCS), 432–440. doi:https://doi.org/10.1007/978-3-642-39137-8-48
  • Lowenstein, H., & Lev-On, A. (2018). Complementing or Substituting? News in an era of multiple platforms and second screens. International Journal of Human Computer Interaction.
  • Lumezanu, C., Feamster, N., & Klein, H., 2012, May. # bias: Measuring the tweeting behavior of propagandists. In Sixth International AAAI Conference on Weblogs and Social Media.
  • Malinen, S. (2015). Understanding user participation in online communities: A systematic literature review of empirical studies. Computers in Human Behavior, 46(June), 228–238. doi:10.1016/j.chb.2015.01.004
  • Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E., & Zhang, M. (2013). Managing customer relationships in the social media era: Introducing the social CRM house. Journal of Interactive Marketing, 27(4), 270–280. doi:10.1016/j.intmar.2013.09.008
  • Markham, A., & Buchanan, E. (2012). Ethical Decision-Making and Internet Research Recommendations from the AoIR ethics working committee. In Recommendations from the AoIR ethics working committee (Version 2.0). Chicago, IL: Association of Internet Researchers. Retrieved from www.aoir.org
  • McCay-Peet, L., & Quan-Haase, A. (2017). What is social media and what questions can social media research help us answer?. In L. Sloan & A. Quan-Haase (Eds.), The SAGE handbook of social media research methods (pp. 13–26). London, UK: SAGE.
  • McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27(1), 415–444. doi:10.1146/annurev.soc.27.1.415
  • Mejova, Y., & Srinivasan, P., 2012, June. Political speech in social media streams: YouTube comments and Twitter posts. In Proceedings of the 4th Annual ACM Web Science Conference(pp. 205–208). ACM.
  • Mislove, A., Lehmann, S., Ahn, Y. Y., Onnela, J. P., & Rosenquist, J. N. (2011). Understanding the demographics of Twitter users. Barcelona, Spain: ICWSM, 11, p.5th.
  • Moreno, M. A., Goniu, N., Moreno, P. S., & Diekema, D. (2013). Ethics of social media research: Common concerns and practical considerations. Cyberpsychology, Behavior, and Social Networking, 16(9), 708–713. doi:10.1089/cyber.2012.0334
  • Morstatter, F., Pfeffer, J., & Liu, H., 2014, April. When is it biased?: Assessing the representativeness of Twitter’s streaming API. In Proceedings of the 23rd international conference on world wide web (pp. 555–556). ACM.
  • Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13–46. doi:10.2501/IJA-30-1-013-046
  • Nagpal, C., Boecking, B., Miller, K., & Dubrawski, A. (2016). personaLink. In A tool to link users across online forums. Pittsburgh, USA: Robotics Institute
  • Narimatsu, H., Sugawara, Y., & Fukao, A. (2012). Cancer patients on twitter: The novel communities on social media. Annals of Oncology. 23, xi109. Retrieved from http://www.embase.com/search/results?subaction=viewrecord&from=export&id=L71792037%5Cnhttp://dx.doi.org/10.1093/annonc/mds572%5Cnhttp://sfx.metabib.ch/sfx_uzh?sid=EMBASE&sid=EMBASE&issn=09237534&id=doi:10.1093%2Fannonc%2Fmds572&atitle=Cancer+patients+on+twitter
  • Noë, N., Whitaker, R. M., Chorley, M. J., & Pollet, T. V. (2016). Birds of a feather locate together? Foursquare checkins and personality homophily. Computers in Human Behavior, 58, 343–353. doi:10.1016/j.chb.2016.01.009
  • Noulas, A., Scellato, S., Lambiotte, R., Pontil, M., & Mascolo, C. (2012). A tale of many cities: Universal patterns in human urban mobility. PLoS ONE, 7, 5. http://doi.org/10.1371/journal.pone.0037027
  • Oh, S., & Syn, S. Y. (2015). Motivations for sharing information and social support in social media: A comparative analysis of Facebook, Twitter, delicious, YouTube, and Flickr. Journal of the Association for Information Science and Technology, 66(10), 2045–2060. doi:10.1002/asi.2015.66.issue-10
  • Panek, E. T., Nardis, Y., & Konrath, S. (2013). Mirror or Megaphone?: How relationships between narcissism and social networking site use differ on Facebook and Twitter. Computers in Human Behavior, 29(5), 2004–2012. doi:10.1016/j.chb.2013.04.012
  • Pappalardo, L., Rossetti, G., & Pedreschi, D., 2012, August. “How well do we know each other?” Detecting Tie Strength in Multidimensional Social Networks. In Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on (pp. 1040–1045). IEEE.
  • Pedrana, A., Hellard, M., Gold, J., Ata, N., Chang, S., Howard, S., … Stoove, M. (2013). Queer as F** k: Reaching and engaging gay men in sexual health promotion through social networking sites. Journal of Medical Internet Research, 15, 2. doi:10.2196/jmir.2334
  • Phethean, C., Tiropanis, T., & Harris, L. (2015). Assessing the value of social media for organisations : The case for charitable use uses of social media. In WebSci Vol. 15. Oxford, UK: ACM Press. https://doi.org/http://dx.doi.org/10.1145/2786451.2786457
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879. doi:10.1037/0021-9010.88.5.879
  • Poell, T., & Borra, E. (2012). Twitter, YouTube, and Flickr as platforms of alternative journalism: The social media account of the 2010 Toronto G20 protests. Journalism, 13(6), 695–713. doi:10.1177/1464884911431533
  • Pontes, T., Magno, G., Vasconcelos, M., Gupta, A., Almeida, J., Kumaraguru, P., & Almeida, V. (2012). Beware of what you share: Inferring home location in social networks. Proceedings - 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012, 571–578. http://doi.org/10.1109/ICDMW.2012.106
  • Qi, G. J., Aggarwal, C. C., & Huang, T., 2013, April. Link prediction across networks by biased cross-network sampling. In Data Engineering (ICDE), 2013 IEEE 29th International Conference on (pp. 793–804). IEEE.
  • Quan-Haase, A., & Young, A. L. (2010). Uses and gratifications of social media: A comparison of Facebook and instant messaging. Bulletin of Science. Technology & Society, 30(5), 350–361.
  • Rao, L. (2012) Instagram photos will no longer appear In Twitter Streams At All, TechCrunch (Online) Available at: https://techcrunch.com/2012/12/09/it-appears-that-instagram-photos-arent-showing-up-in-twitter-streams-at-all/
  • Ratkiewicz, J., Conover, M. D., Meiss, M., Gonc, B., Flammini, A., & Menczer, F. (2011). Detecting and tracking political abuse in social media. Artificial Intelligence, 297–304. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/viewFile/2850/3274
  • Rhiu, I., & Hwan Yun, M. (2018). Exploring user experience of smartphones in social media: A mixed-method analysis. International Journal of Human Computer Interaction, 2018.
  • Rose, C. (2011). The security implications of ubiquitous social media. International Journal of Management and Information Systems, 15(1), 35.
  • Rost, M., Barkhuus, L., Cramer, H., & Brown, B., 2013, February. Representation and communication: Challenges in interpreting large social media datasets. In Proceedings of the 2013 conference on Computer supported cooperative work (pp. 357–362). ACM.
  • Ruehl, C. H., & Ingenhoff, D. (2015). Communication management on social networking sites: Stakeholder motives and usage types of corporate Facebook, Twitter and YouTube pages. Journal of Communication Management, 19(3), 288–302. doi:10.1108/JCOM-04-2015-0025
  • Ruppert, E. (2013). Rethinking empirical social sciences. Dialogues in Human Geography, 3(3), 268–273. doi:10.1177/2043820613514321
  • Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063–1064. doi:10.1126/science.346.6213.1
  • Saez-Trumper, D., Castillo, C., & Lalmas, M. (2013, October). Social media news communities: Gatekeeping, coverage, and statement bias. In Proceedings of the 22nd ACM international conference on Conference on information & knowledge management. San Francisco, USA:ACM: 1679–1684.
  • Schacht, J., Hall, M., & Chorley, M. (2015). Tweet if you will – The real question is, who do you influence? WebSci, 15, Article 55. doi:https://doi.org/10.1145/2786451.2786923
  • Schmidt, A. L., Zollo, F., Del Vicario, M., Bessi, A., Scala, A., Caldarelli, G., … Quattrociocchi, W., 2017. Anatomy of news consumption on Facebook. Proceedings of the National Academy of Sciences, p.201617052.
  • Schroeder, R. (2014). Big data and the brave new world of social research. Big Data & Society, 1(2), 2053951714563194. https://doi.org/10.1177/2053951714563194.
  • Schwarz, N., Hippler, H. J., Deutsch, B., & Strack, F. (1985). Response scales: Effects of category range on reported behavior and comparative judgments. Public Opinion Quarterly, 49(3), 388–395. doi:10.1086/268936
  • Silva, T. H., vaz de Melo, P., O. S., Almeida, J., M., Salles, J., & Loureiro, A. A. F. (2013). A comparison of Foursquare and Instagram to the study of city dynamics and urban social behaviour. Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing - UrbComp, ’13, 1–8. doi:http://doi.org/10.1145/2505821.2505836 July 2014
  • Silverman, C., & Singer-Vine, J. (2016). Most Americans who see fake news believe it, new survey says. Buzzfeed, 1–14. Retrieved from https://online225.psych.wisc.edu/wp-content/uploads/225-Master/225-UnitPages/Unit-02/Silverman_Singer-Vine_BuzzFeed_2016.pdf%0Ahttps://www.buzzfeed.com/craigsilverman/fake-news-survey?utm_source=API+Need+to+Know+newsletter&utm_campaign=83c0a6de60-EMAIL_CA
  • Skeels, M. M., & Grudin, J. (2009). when social networks cross boundaries: a case study of workplace use of Facebook and Linkedin. Proceedings of the ACM 2009 International Conference on Supporting Group Work, 95–103. http://doi.org/10.1145/1531674.1531689
  • Sloan, L., Morgan, J., Burnap, P., & Williams, M. (2015). Who tweets? Deriving the demographic characteristics of age, occupation and social class from twitter user meta-data. Plos One, 10(3), e0115545. doi:http://doi.org/10.1371/journal.pone.0115545
  • Sloan, L., Morgan, J., Housley, W., Williams, M., Edwards, A., Burnap, P., & Rana, O. (2013). Knowing the Tweeters: Deriving sociologically relevant demographics from Twitter. Sociological Research Online, 18(3), 1–11. doi:10.5153/sro.3001
  • Sloan, L., & Quan-Haase, A. (2017). The SAGE handbook of social media research methods. Retrieved from https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-media-research-methods/book245370
  • Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 102–113. doi:10.1016/j.intmar.2012.01.002
  • Sorensen, L., 2009, May. User managed trust in social networking-Comparing Facebook, MySpace and Linkedin. In Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology, 2009. Wireless VITAE 2009. 1st International Conference on (pp. 427–431). IEEE.
  • Starbird, K., Muzny, G., & Palen, L. (2012). Learning from the crowd: Collaborative filtering techniques for identifying on-the-ground Twitterers during mass disruptions. Proceedings of 9th International Conference on Information Systems for Crisis Response and Management, ISCRAM, 2011 (April), 1–10.
  • Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29(6), 434–445. doi:10.1016/j.appdev.2008.07.002
  • Thorson, K., Driscoll, K., Ekdale, B., Edgerly, S., Thompson, L. G., Schrock, A., & Wells, C. (2013). YouTube, Twitter and the occupy movement: Connecting content and circulation practices. Information, Communication & Society, 16(3), 421-451.
  • Tresp, V., Marc Overhage, J., Bundschus, M., Rabizadeh, S., Fasching, P. A., & Yu, S. (2016). Going digital: A survey on digitalization and large-scale data analytics in healthcare. Proceedings of the IEEE, 104( 11),2180–2206. https://doi.org/10.1109/JPROC.2016.2615052
  • Tufekci, Z. (2014). Big questions for social media big data: Representativeness, validity and other methodological pitfalls. ICWSM, 14, 505–514.
  • Tyson, G., Perta, V. C., Haddadi, H., & Seto, M. C. (2016). A first look at user activity on tinder. ASONAM, 2016, 1–8. doi:http://doi.org/10.1109/ASONAM.2016.7752275
  • van Dijck, J. (2013). ‘You have one identity’: Performing the self on Facebook and LinkedIn. Media, Culture & Society, 35(2), 199–215. doi: 10.1177/0163443712468605
  • Vosecky, J., Hong, D., & Shen, V. Y. (2009). User identification across multiple social networks. In Proceedings of the First International Conference on Networked Digital Technologies (pp. 360–365). New York, NY, USA: IEEE. http://doi.org/10.1109/NDT.2009.5272173
  • Walker, C., & Alrehamy, H. (2015). Personal data lake with data gravity pull. Proceedings - 2015 IEEE 5th International Conference on Big Data and Cloud Computing, BDCloud 2015, 160–167. http://doi.org/10.1109/BDCloud.2015.62
  • Wang, P., He, W., & Zhao, J. (2014). A tale of three social networks: User activity comparisons across Facebook, Twitter, and Foursquare. IEEE Internet Computing, 18(2), 10–15. doi:10.1109/MIC.2013.128
  • Xu, J., Lu, T.-C., Compton, R., & Allen, D. (2014). Quantifying cross-platform engagement through large-scale user alignment. In Proceedings of the 2014 ACM Conference on Web Science (pp. 281–282). New York, NY, USA: ACM.
  • Yan, M., Sang, J., Mei, T., & Xu, C. (2013). Friend transfer: Cold-start friend recommendation with cross-platform transfer learning of social knowledge. Proceedings - IEEE International Conference on Multimedia and Expo. http://doi.org/10.1109/ICME.2013.6607510
  • Zafarani, R., & Liu, H. (2013). Connecting users across social media sites: A behavioral-modeling approach. Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’13, 41. http://doi.org/10.1145/2487575.2487648
  • Zhang, J., Kong, X., & Philip, S. Y., 2013, December. Predicting social links for new users across aligned heterogeneous social networks. In Data Mining (ICDM), 2013 IEEE 13th International Conference on (pp. 1289–1294). IEEE.
  • Zhang, J., & Yu, P. S. (2015). Multiple anonymized social networks alignment. In 2015 IEEE International Conference on Data Mining (pp. 599–608). IEEE. http://doi.org/10.1109/ICDM.2015.114
  • Zimmer, M. (2010). “But the data is already public”: On the ethics of research in Facebook. Ethics and Information Technology, 12(4), 313–325. doi:10.1007/s10676-010-9227-5

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