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nowUP: A System that Automatically Creates TV Summaries Based on Twitter Activity

  • Pedro Almeida
  • Jorge Ferraz de Abreu
  • Rita Oliveira
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 689)

Abstract

Users post a lot of related TV information on social networks while they are watching TV, mostly in a connected way with the highlight moments of the TV shows. This paper reports on the nowUP project, targeted at the development of a service that automatically creates summaries of TV programs based on the buzz on social networks. The project premise relies on the idea that social media buzz has the potential to be used as an automatic editorial criterion. In this framework, the project goals include the development of a solution that automatically produces TV summaries of popular television programs (like football matches, talent or reality shows) based on the Twitter activity. The solution is based on a data-mining engine that processes the activity of this social network looking for tweets related with TV shows. Based on the program metadata it indexes the twitter activity; correlates tweets; and creates clusters of peaks, being the relevant clusters associated with the TV highlights. With this, a specific developed video engine automatically edits and creates a full video summary (an edited sequence of TV highlights) and publishes it in an online platform. The paper reports on the solution architecture and features and on the results of its preliminary evaluation. The results show that the solution was very successful in achieving the project main goal and the users are willing to have access to this type of social buzz-based video summaries.

Keywords

TV summaries Highlights Editing Twitter Evaluation 

Notes

Acknowledgements

The authors would like to acknowledge the remaining partners of the nowUP project (Altice Labs and Telecommunications Institute).

References

  1. 1.
    Forlines, C., Peker, K., Divakaran, A.: Subjective assessment of consumer video summarization. In: SPIE Proceedings - Special Session: Evaluating Video Summarization, Browsing, and Retrieval Techniques, vol. 6073 (2006). doi: 10.1117/12.648554
  2. 2.
    Abreu, J., et al.: Survey of Catch-up TV and other time-shift services: a comprehensive analysis and taxonomy of linear and nonlinear television. Telecommun. Syst. 64, 1–18 (2016). doi: 10.1007/s11235-016-0157-3 Google Scholar
  3. 3.
    Viacom, When Networks Network - TV Gets Social (2013). http://vimninsights.viacom.com/post/61773538381/when-networks-network-tv-gets-social-in-our. Last accessed 1 Mar 2017
  4. 4.
    Nielsen Social, TV Season in Review: Biggest Moments on Twitter (2015). http://www.nielsensocial.com/tv-season-in-review-biggest-moments-on-twitter/. Last accessed 1 Mar 2017
  5. 5.
    Kantar Media, Who’s Tweeting about TV in the UK? (2015). http://www.kantarmedia.com/uk/thinking-resources/latest-thinking/who-is-tweeting-about-tv-in-the-uk. Last accessed 1 Mar 2017
  6. 6.
    Capon, G.: Twitter Amplify will create enormous value for broadcasters and brands (2014). http://www.theguardian.com/media-network/media-network-blog/2014/may/23/twitter-amplify-influence-tv. Last accessed 1 Mar 2017
  7. 7.
    Twitter Amplify, Twitter Amplify Product Video (2014). https://twitter.com/twitteramplify/status/516981620448845825. Last accessed 21 Jan 2016
  8. 8.
    Wildmoka, Platform (2014). http://wildmoka.com/platform/. Last accessed 21 Jan 2016
  9. 9.
    Wildmoka, Press Release – CANAL+ Group selects Moments Share (2014). http://wildmoka.com/press-release-canal-group-selects-moments-share-wildmokas-social-tv-solution/. Last accessed 21 Jan 2016
  10. 10.
    Wildmoka, Moments Share (2014). http://wildmoka.com/solutions/moments-share/. Last accessed 21 Jan 2016
  11. 11.
    Wildmoka, Moments Replay (2014). http://wildmoka.com/solutions/moments-replay/. Last accessed 21 Jan 2016
  12. 12.
    Wildmoka, Moments Capture (2014). http://wildmoka.com/solutions/moments-capture/. Last accessed 21 Jan 2016
  13. 13.
    Tellyo, Tellyo –Media sharing (2017). https://tellyo.com/. Last accessed 1 Mar 2017
  14. 14.
    Ulanoff, L.: Twitter experiments with TV Timelines (2015). http://mashable.com/2015/03/12/twitter-experiment-tv-timelines/#Ip8nGr1eJqq3. Last accessed 21 Jan 2016
  15. 15.
    Nielsen Social, Nielsen Social – Social TV Analytics & Solutions (2017). http://www.nielsensocial.com/. Last accessed 1 Mar 2017
  16. 16.
    Nielsen Social, Products – Nielsen Social (2017). http://www.nielsensocial.com/products/. Last accessed 1 Mar 2017
  17. 17.
    Beuker, I.: The Social EPG: The Next Step Towards Social TV? (2012). http://www.viralblog.com/social-tv/the-social-epg-the-next-step-towards-social-tv/. Last accessed 1 Mar 2017
  18. 18.
    Jiang, W., Cotton, C., Loui, A.C.: Automatic consumer video summarization by audio and visual analysis. In: Proceedings of International Conference on Multimedia and Expo (ICME), pp. 1–6 (2011). doi: 10.1109/ICME.2011.6011841
  19. 19.
    Alonso, O., Shiells, K.: Timelines as summaries of popular scheduled events. In: Proceedings of the 22nd International World Wide Web Conference Committee (IW3C2), pp. 1037–1044 (2013). doi: 10.1145/2487788.2488114
  20. 20.
    Flick, U.: An Introduction to Qualitative Research, 4th edn. Sage Publications, London (2009)Google Scholar
  21. 21.
    Bradley, M., Lang, P.: Measuring emotion: the self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry 25(1), 49–59 (1994). http://www.ncbi.nlm.nih.gov/pubmed/7962581 CrossRefGoogle Scholar
  22. 22.
    Outhwaite, W., Turner, S.: The Sage Handbook of Social Science Methodology, 1st edn. Sage Publications, London (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of Aveiro - DigimediaAveiroPortugal

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