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Semantic Aggregation and Zooming of User Viewpoints in Social Media Content

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User Modeling, Adaptation, and Personalization (UMAP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7899))

Abstract

Social web provides rich content for gaining an understanding about the users which can empower adaptation. There is a current trend to extract user profiles from social media content using semantic augmentation and linking to domain ontologies. The paper shows a further step in this research strand, exploiting semantics to get a deeper understanding about the users by extracting the domain regions where the users focus, which are defined as viewpoints. The paper outlines a formal framework for extracting viewpoints from semantic tags associated with user comments. This enables zooming into the viewpoints at different aggregation layers, as well as comparing users on the basis of the areas where they focus. The framework is applied on YouTube content, illustrating an insight into emotions users refer to in their comments on job interview videos.

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References

  1. Abel, F., Herder, E., Houben, G.-J., Henze, N., Krause, D.: Cross-system user modeling and personalization on the Social Web. User Modeling and User-Adapted Interaction, 1–41 (2012)

    Google Scholar 

  2. Bontcheva, K., Rout, D.: Making Sense of Social Media Streams through Semantics: a Survey. Semantic Web Journal (to appear)

    Google Scholar 

  3. Resnick, P.: Keynote: Personalised Filters Yes; Bubbles No. In: 19th International Conference on User Modeling, Adaptation, and Personalization (UMAP) (2011)

    Google Scholar 

  4. ACM, http://acmrecsys.wordpress.com/2011/10/25/panel-on-the-filter-bubble/

  5. Gao, Q., Abel, F., Houben, G.-J., Yu, Y.: A Comparative Study of Users’ Microblogging Behavior on Sina Weibo and Twitter. In: Masthoff, J., Mobasher, B., Desmarais, M.C., Nkambou, R. (eds.) UMAP 2012. LNCS, vol. 7379, pp. 88–101. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  6. Carmagnola, F., Cena, F., Console, L., Cortassa, O., Gena, C., Goy, A., Torre, I., Toso, A., Vernero, F.: Tag-based user modeling for social multi-device adaptive guides. User Modeling and User-Adapted Interaction 18, 497–538 (2008)

    Article  Google Scholar 

  7. Alonso, J.B., Havasi, C., Lieberman, H.: PerspectiveSpace: Opinion Modeling with Dimensionality Reduction. In: Houben, G.-J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) UMAP 2009. LNCS, vol. 5535, pp. 162–172. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. Paul, M.J., Zhai, C., Girju, R.: Summarizing contrastive viewpoints in opinionated text. In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 66–76. Association for Computational Linguistics, Cambridge (2010)

    Google Scholar 

  9. Fang, Y., Si, L., Somasundaram, N., Yu, Z.: Mining contrastive opinions on political texts using cross-perspective topic model. In: Proceedings of the Fifth ACM International Conference on Web Search and Data Mining, pp. 63–72. ACM, Seattle (2012)

    Chapter  Google Scholar 

  10. Bizău, A., Rusu, D., Mladenic, D.: Expressing Opinion Diversity. In: First International Workshop on Knowledge Diversity on the Web (DiversiWeb 2011), 20th World Wide Web Conference (WWW 2011), Hyderabad, India (2011)

    Google Scholar 

  11. Pochampally, R., Karlapalem, K.: Mining Diverse Views from Related Articles. In: First International Workshop on Knowledge Diversity on the Web (DiversiWeb 2011), 20th World Wide Web Conference (WWW 2011), Hyderabad, India (2011)

    Google Scholar 

  12. Kang, J.-H., Lerman, K.: Leveraging User Diversity to Harvest Knowledge on the Social Web. In: The Third IEEE International Conference on Social Computing (SocialCom 2011), Boston, USA (2011)

    Google Scholar 

  13. Wille, R.: Formal Concept Analysis as Mathematical Theory of Concepts and Concept Hierarchies. In: Ganter, B., Stumme, G., Wille, R. (eds.) Formal Concept Analysis. LNCS (LNAI), vol. 3626, pp. 1–33. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  14. Cimiano, P., Hotho, A., Stumme, G., Tane, J.: Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies. In: Eklund, P. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 189–207. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  15. Yun, Z., Boqin, F.: Tag-based user modeling using formal concept analysis. In: 8th IEEE International Conference on Computer and Information Technology (CIT), pp. 485–490 (2008)

    Google Scholar 

  16. Kim, S., Hall, W., Keane, A.: Using Document Structures for Personal Ontologies and User Modeling. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds.) UM 2001. LNCS (LNAI), vol. 2109, pp. 240–242. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  17. Despotakis, D., Thakker, D., Dimitrova, V., Lau, L.: Diversity of user viewpoints on social signals: a study with YouTube content. In: International Workshop on Augmented User Modeling (AUM) in UMAP, Montreal, Canada (2012)

    Google Scholar 

  18. Thakker, D., Despotakis, D., Dimitrova, V., Lau, L., Brna, P.: Taming digital traces for informal learning: a semantic-driven approach. In: Ravenscroft, A., Lindstaedt, S., Kloos, C.D., Hernández-Leo, D. (eds.) EC-TEL 2012. LNCS, vol. 7563, pp. 348–362. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

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Despotakis, D., Dimitrova, V., Lau, L., Thakker, D. (2013). Semantic Aggregation and Zooming of User Viewpoints in Social Media Content. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_5

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  • DOI: https://doi.org/10.1007/978-3-642-38844-6_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38843-9

  • Online ISBN: 978-3-642-38844-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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