Skip to main content
SpringerLink
Log in

Predicting Audience Engagement Across Social Media Platforms in the News Domain

  • Conference paper
  • First Online:
Social Informatics (SocInfo 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11864))

Included in the following conference series:

Abstract

We analyze cross-platform factors for posts on both single and multiple social media platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social media posts from 53 news outlets during eight months on four social media platforms (Facebook, Instagram, Twitter, and YouTube), along with the associated comments (more than 31 million) and the number of likes (more than 840 million). We develop a framework for predicting the audience engagement based on both linguistic features of the post and social media platform factors. Among other findings, results show that content with high engagement on one platform does not guarantee high engagement on another platform, even when news outlets use similar cross-platform posts; however, for some content, cross-sharing posts on a platform will increase overall audience engagement on another platform. As one of the few multiple social media platform studies, the findings have implications for the news domain, as well as other fields that distribute online content via social media.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The threshold was chosen based on our manual inspection of 600 randomly selected pairs.

References

  1. The Top 25 (2011). https://www.journalism.org/2011/05/09/top-25/. Accessed 15 Apr 2019

  2. Aldous, K.K., An, J., Jansen, B.J.: The challenges of creating engaging content : results from a focus group study of a popular news media organization. In: ACM CHI (2019)

    Google Scholar 

  3. Aldous, K.K., An, J., Jansen, B.J.: View, like, comment, post: analyzing user engagement by topic at 4 levels across 5 social media platforms for 53 news organizations. In: ICWSM (2019)

    Google Scholar 

  4. Alvarez, J.J., Mendoza, F.A., Labrador, M.: An accurate way to cross reference users across social networks. In: SoutheastCon. IEEE (2017)

    Google Scholar 

  5. An, J., Cha, M., Gummadi, P.K., Crowcroft, J.: Media landscape in Twitter: a world of new conventions and political diversity. In: ICWSM (2011)

    Google Scholar 

  6. An, J., Quercia, D., Crowcroft, J.: Partisan sharing: Facebook evidence and societal consequences. In: COSN. ACM (2014)

    Google Scholar 

  7. An, J., Weber, I.: Diversity in online advertising: a case study of 69 brands on social media. In: Staab, S., Koltsova, O., Ignatov, D.I. (eds.) SocInfo 2018. LNCS, vol. 11185, pp. 38–53. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01129-1_3

    Chapter  Google Scholar 

  8. Balbi, S., Misuraca, M., Scepi, G.: Combining different evaluation systems on social media for measuring user satisfaction. Inf. Process. Manag. 54(4), 674–685 (2018)

    Article  Google Scholar 

  9. Barrón-Cedeo, A., Jaradat, I., Martino, G.D.S., Nakov, P.: Proppy: organizing the news based on their propagandistic content. Inf. Process. Manag. 56(5), 1849–1864 (2019)

    Google Scholar 

  10. Brems, C., Temmerman, M., Graham, T., Broersma, M.: Personal branding on Twitter. Digit. J. 5(4), 443–459 (2017)

    Google Scholar 

  11. Castillo, C., El-Haddad, M., Pfeffer, J., Stempeck, M.: Characterizing the life cycle of online news stories using social media reactions. In: CSCW. ACM (2014)

    Google Scholar 

  12. Constantinides, M., Dowell, J.: A framework for interaction-driven user modeling of mobile news reading behaviour. In: UMAP. ACM (2018)

    Google Scholar 

  13. Dragoni, M., Federici, M., Rexha, A.: An unsupervised aspect extraction strategy for monitoring real-time reviews stream. Inf. Process. Manag. 56(3), 1103–1118 (2019)

    Article  Google Scholar 

  14. Farahbakhsh, R., Cuevas, A., Crespi, N.: Characterization of cross-posting activity for professional users across Facebook, Twitter and Google+. Soc. Netw. Anal. Min. 6(1), 33 (2016)

    Article  Google Scholar 

  15. Fletcher, R., Nielsen, R.K.: Are people incidentally exposed to news on social media? a comparative analysis. New Media Soc. 20(7), 2450–2468 (2018)

    Article  Google Scholar 

  16. Gottfried, J., Sheare, E.: News use across social media platforms 2016. State of the News Media, pp. 1–20 (2016)

    Google Scholar 

  17. Hladk, R., Štětka, V.: The powers that tweet. J. Stud. 18(2), 154–174 (2017)

    Google Scholar 

  18. Hussein, R., Hassan, S.: Customer engagement on social media: how to enhance continuation of use. Online Inf. Rev. 41(7), 1006–1028 (2017)

    Article  Google Scholar 

  19. Kallas, P.: Top 15 most popular social networking sites, July 2017 (2017). http://www.ebizmba.com/articles/social-networking-websites. Accessed 19 Aug 2018

  20. Kim, S.M., et al.: Twitter content eliciting user engagement: a case study on Australian organisations. In: WWW. ACM (2017)

    Google Scholar 

  21. Ksiazek, T.B., Peer, L., Lessard, K.: User engagement with online news: conceptualizing interactivity and exploring the relationship between online news videos and user comments. New Media Soc. 18(3), 502–520 (2016)

    Article  Google Scholar 

  22. Lalmas, M., O’Brien, H., Yom-Tov, E.: Measuring user engagement. Synth. Lect. Inf. Concepts, Retrieval Serv. 6(4), 1–132 (2014)

    Google Scholar 

  23. Lee, R.K.W., Hoang, T.A., Lim, E.P.: On analyzing user topic-specific platform preferences across multiple social media sites. In: WWW (2017)

    Google Scholar 

  24. Lim, B.H., Lu, D., Chen, T., Kan, M.Y.: # mytweet via instagram: exploring user behaviour across multiple social networks. In: ASONAM. ACM (2015)

    Google Scholar 

  25. Mele, I., Bahrainian, S.A., Crestani, F.: Event mining and timeliness analysis from heterogeneous news streams. Inf. Process. Manag. 56(3), 969–993 (2019)

    Article  Google Scholar 

  26. Mitchell, A., Holcomb, J., Weisel, R.: Data and trends about key sectors in the U.S. news media industry. State of the News Media, pp. 1–118 (2016)

    Google Scholar 

  27. Mukherjee, P., Jansen, B.J.: Conversing and searching: the causal relationship between social media and web search. Internet Res. 27(5), 1209–1226 (2017)

    Article  Google Scholar 

  28. Mukherjee, P., Jansen, B.J.: Information sharing by viewers via second screens for in-real-life events. Trans. Web 11(1), 1:1–1:24 (2017)

    Google Scholar 

  29. Muñoz Expósito, M., Oviedo-García, M., Castellanos-Verdugo, M.: How to measure engagement in Twitter: advancing a metric. Internet Res. 27, 1122–1148 (2017)

    Article  Google Scholar 

  30. Napoli, P.M.: Audience Evolution: New Technologies and the Transformation of Media Audiences. Columbia University Press, New York (2011)

    Google Scholar 

  31. Nicolae, M.: 2016’s best news sites (2016). https://wallethub.com/blog/best-news-sites/21699/. Accessed 15 Apr 2019

  32. O’Brien, H.L., Toms, E.G.: What is user engagement? a conceptual framework for defining user engagement with technology. Am. Soc. Inf. Sci. Technol. 59(6), 938–955 (2008)

    Article  Google Scholar 

  33. Picone, I., Courtois, C., Paulussen, S.: When news is everywhere: understanding participation, cross-mediality and mobility in journalism from a radical user perspective. J. Pract. 9(1), 35–49 (2015)

    Google Scholar 

  34. Schlagwein, D., Hu, M.: How and why organisations use social media: five use types and their relation to absorptive capacity. J. Inf. Technol. 32(2), 194–209 (2017)

    Article  Google Scholar 

  35. Shearer, E., Gottfried, J.: News use across social media platforms 2017. Pew Research Center (2017)

    Google Scholar 

  36. Smith, A.N., Fischer, E., Yongjian, C.: How does brand-related user-generated content differ across Youtube, Facebook, and Twitter? J. Interact. Mark. 26(2), 102–113 (2012)

    Article  Google Scholar 

  37. Stocking, G.: Digital news fact sheet. State of the News Media, pp. 1–2 (2017)

    Google Scholar 

  38. Swart, J., Peters, C., Broersma, M.: Navigating cross-media news use: media repertoires and the value of news in everyday life. J. Stud. 18(11), 1343–1362 (2017)

    Google Scholar 

  39. Zhong, C., Chan, H.w., Karamshuk, D., Lee, D., Sastry, N.: Wearing many (social) hats: how different are your different social network personae? In: ICWSM (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

    Kholoud Khalil Aldous

  2. Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar

    Jisun An & Bernard J. Jansen

Authors
  1. Kholoud Khalil Aldous
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jisun An
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bernard J. Jansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kholoud Khalil Aldous .

Editor information

Editors and Affiliations

  1. Qatar Computing Research Institute, Doha, Qatar

    Ingmar Weber

  2. Qatar Computing Research Institute, Doha, Qatar

    Kareem M. Darwish

  3. University of Koblenz-Landau, Koblenz, Germany

    Claudia Wagner

  4. Max Planck Institute for Demographic Research, Rostock, Germany

    Emilio Zagheni

  5. Northeastern University, Boston, MA, USA

    Laura Nelson

  6. Max Planck Institute for Demographic Research, Rostock, Germany

    Samin Aref

  7. GESIS-Leibniz Institute for the Social Sciences, Cologne, Germany

    Fabian Flöck

A The list of news outlets

A The list of news outlets

The list of the 53 news outlets is shown in Table 8:

Table 8. List of 53 online news organizations
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aldous, K.K., An, J., Jansen, B.J. (2019). Predicting Audience Engagement Across Social Media Platforms in the News Domain. In: Weber, I., et al. Social Informatics. SocInfo 2019. Lecture Notes in Computer Science(), vol 11864. Springer, Cham. https://doi.org/10.1007/978-3-030-34971-4_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-34971-4_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34970-7

  • Online ISBN: 978-3-030-34971-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation