Lynda Tamine
ABSTRACT
The notion of implicit (or explicit) collaborative information access refers to systems and practices allowing a group of users to unintentionally (respectively intentionally) seek, share and retrieve information to achieve similar (respectively shared) information-related goals. Despite an increasing adoption in social environments, collaboration behavior in information seeking and retrieval is mainly limited to small-sized groups, generally restricted to working spaces. Much remains to be learned about collaborative information seeking within open web social spaces. This paper is an attempt to better understand either implicit or explicit collaboration by studying Twitter, one of the most popular and widely used social networks. We study in particular the complex intertwinement of human interactions induced by both collaboration and social networking. We empirically explore explicit collaborative interactions based on focused conversation streams during two crisis. We identify structural patterns of temporally representative conversation subgraphs and represent their topics using Latent Dirichlet Allocation (LDA) modeling. Our main findings suggest that: 1) the critical mass of collaboration is generally limited to small-sized flat networks, with or without an influential user, 2) users are active as members of weakly overlapping groups and engage in numerous collaborative search and sharing tasks dealing with different topics, and 3) collaborative group ties evolve within the time-span of conversations.
- A. Acar and Y. Muraki. Twitter for crisis communication: Lessons learned from japan tsunami disaster. Int. J. Web Based Communities, 7(3):392--402, 2011. Google Scholar
Digital Library
- I. Badache and M. Boughanem. Harnessing social signals to enhance a search. In WI, volume 1, pages 303--309, Aug 2014. Google ScholarDigital Library
- R. Baeza-Yates and D. Saez-Trumper. Wisdom of the crowd or wisdom of a few? an analysis of users' content generation. In Hypertext and Social Media, pages 69--74. ACM, 2015. Google ScholarDigital Library
- D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. J. Mach. Learn. Res., 3:993--1022, 2003. Google ScholarCross Ref
- R. D. Bock and S. Z. Husain. An adaptation of holzinger's b-coefficients for the analysis of sociometric data. Sociometry, 13(2):pp. 146--153, 1950.Google ScholarCross Ref
- F. Cacheda, V. Carneiro, D. Fernández, and V. Formoso. Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems. ACM Trans. Web, 5(1):2:1--2:33, Feb. 2011. Google ScholarDigital Library
- D. Carmel, N. Zwerdling, I. Guy, S. Ofek-Koifman, N. Har'el, I. Ronen, E. Uziel, S. Yogev, and S. Chernov. Personalized social search based on the user's social network. In CIKM, pages 1227--1236. ACM, 2009. Google ScholarDigital Library
- C. Castillo, M. Mendoza, and B. Poblete. Information credibility on twitter. In WWW, pages 675--684. ACM, 2011. Google ScholarDigital Library
- P. Cogan, M. Andrews, M. Bradonjic, W. S. Kennedy, A. Sala, and G. Tucci. Reconstruction and analysis of twitter conversation graphs. In HotSocial Workshop, pages 25--31. ACM, 2012. Google ScholarDigital Library
- M. De Choudhury, M. R. Morris, and R. W. White. Seeking and sharing health information online: Comparing search engines and social media. In CHI. ACM, 2014. Google ScholarDigital Library
- K. Ehrlich and N. S. Shami. Microblogging inside and outside the workplace. In ICWSM. The AAAI Press, 2010.Google Scholar
- I. Eleta and J. Golbeck. Multilingual use of twitter: Social networks at the language frontier. Computers in Human Behavior, 41:424--432, 2014. Google ScholarDigital Library
- B. M. Evans and E. H. Chi. Towards a model of understanding social search. In CSCW, pages 485--494. ACM, 2008. Google ScholarDigital Library
- J. Foster. Collaborative information seeking and retrieval. Annual Rev. Info. Sci & Technol., 40(1), Dec. 2006.Google Scholar
- L. Franco and H. Kawai. News detection in the blogosphere: Two approaches based on structure and content analysis. In ICWSM, 2010.Google Scholar
- J. P. Gene Golovinsky and M. Back. A taxonomy of collaboration in online seeking. In arxiv.org/pdf/0908.0704, CoRR abs/0908.0704, 2009.Google Scholar
- T. Heverin and L. Zach. Use of microblogging for collective sense-making during violent crises: A study of three campus shootings. JASIST, 63(1):34--47, 2012. Google ScholarDigital Library
- S. R. Hiltz, P. Diaz, and G. Mark. Introduction: Social media and collaborative systems for crisis management. ACM Trans. Comput.-Hum. Interact., 18(4):18:1--18:6, 2011. Google ScholarDigital Library
- T. Holderness and E. Turpin. PetaJakarta.org: Assessing the Role of Social Media for Civic Co-Management During Monsoon Flooding in Jakarta, Indonesia. SMART Infrastructure Facility, University of Wollongong, 2015.Google Scholar
- D. Horowitz and S. D. Kamvar. The anatomy of a large-scale social search engine. In WWW, pages 431--440. ACM, 2010. Google ScholarDigital Library
- M. Imran, C. Castillo, F. Diaz, and S. Vieweg. Processing social media messages in mass emergency: A survey. ACM Comput. Surv., 47(4):67:1--67:38, June 2015. Google ScholarDigital Library
- M. Imran, S. Elbassuoni, C. Castillo, F. Diaz, and P. Meier. Practical extraction of disaster-relevant information from social media. In WWW, pages 1021--1024, 2013. Google ScholarDigital Library
- J.-W. Jeong, M. R. Morris, J. Teevan, and D. Liebling. A crowd-powered socially embedded search engine. In ICWSM. AAAI, 2013.Google Scholar
- B. Karweg, C. Huetter, and K. Böhm. Evolving social search based on bookmarks and status messages from social networks. In CIKM, pages 1825--1834. ACM, 2011. Google ScholarDigital Library
- A. Kavanaugh, S. D. Sheetz, F. Quek, and B. J. Kim. Cell phone use with social ties during crises: The case of the virginia tech tragedy. Using Social and Information Technologies for Disaster and Crisis Management, (84), 2013.Google Scholar
- V. Lampos, T. De Bie, and N. Cristianini. Flu detector: Tracking epidemics on twitter. In ECML PKDD, pages 599--602. Springer-Verlag, 2010. Google ScholarDigital Library
- J. Leskovec, M. McGlohon, C. Faloutsos, N. Glance, and M. Hurst. Cascading behavior in large blog graphs. 2007.Google Scholar
- J. T. Meredith Ringel Morris and K. Panovitch. What do people ask their social networks, and why? a survey study of status messages q&a behaviour. In CHI, pages 1739--1748. ACM, 2010. Google ScholarDigital Library
- M. R. Morris. Exploring the complementary roles of social networks and search engines. In ICWSM, 2011.Google Scholar
- M. R. Morris. Collaborative search revisited. In CSCW, pages 1181--1192. ACM, 2013. Google ScholarDigital Library
- F. Morstatter, J. Pfeffer, and H. Liu. When is it biased?: assessing the representativeness of twitter's streaming api. In WWW, 2014. Google ScholarDigital Library
- L. Palen and K. Starbird. Working and sustaining the virtual disaster desk. In CSCW, 2013. Google ScholarDigital Library
- J. Pickens. Social and collaborative information seeking: Panel. In CIKM, pages 2647--2648, New York, NY, USA, 2011. ACM. Google ScholarDigital Library
- S. Poltrock, J. Grudin, S. Dumais, R. Fidel, H. Bruce, and A. M. Pejtersen. Information seeking and sharing in design teams. In SIGGROUP, pages 239--247, 2003. Google ScholarDigital Library
- A. Sadilek, H. A. Kautz, and V. Silenzio. Modeling spread of disease from social interactions. In ICWSM, 2012.Google Scholar
- C. Shah. Collaborative Information Seeking - The Art and Science of Making the Whole Greater than the Sum of All, volume 34 of The information retrieval series. Springer, 2012. Google ScholarDigital Library
- L. Soulier, C. Shah, and L. Tamine. User-driven system-mediated collaborative information retrieval. In SIGIR, pages 485--494, 2014. Google ScholarDigital Library
- L. Soulier, L. Tamine, and W. Bahsoun. On domain expertise-based roles in collaborative information retrieval. IP&M, 50(5):752 -- 774, 2014. Google ScholarDigital Library
- J. Surowiecki. The Wisdow of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations. Random House, pages 78--85, 2004. Google ScholarDigital Library
- J. C. Tang, M. Cebrian, N. A. Giacobe, H.-W. Kim, T. Kim, and D. B. Wickert. Reflecting on the DARPA Red Balloon Challenge. Commun. ACM, 54(4):78--85, 2011. Google ScholarDigital Library
- S. Vieweg, A. L. Hugues, K. Starbird, and L. Paeln. Microblogging during two natural hazards events: What twitter may contribute to situational awarness. In CHI, 2010. Google ScholarDigital Library
- C. Wendling, J. Radisch, and S. Jacobzone. The use of social media in risk and crisis communication. OECD Working Papers on Public Governance, (24), 2013.Google Scholar
Index Terms
- Social Media-Based Collaborative Information Access: Analysis of Online Crisis-Related Twitter Conversations
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