%0 Conference Proceedings %T Social Media-Based Collaborative Information Access: Analysis of Online Crisis-Related Twitter Conversations %+ Recherche d’Information et Synthèse d’Information (IRIT-IRIS) %+ Université Toulouse III - Paul Sabatier (UT3) %+ Machine Learning and Information Access (MLIA) %+ Université Toulouse Capitole (UT Capitole) %+ Systèmes Multi-Agents Coopératifs (IRIT-SMAC) %+ médialab (Sciences Po) (médialab) %+ Centre Marc Bloch (CMB) %A Tamine, Lynda %A Soulier, Laure %A Ben Jabeur, Lamjed %A Amblard, Frédéric %A Hanachi, Chihab %A Hubert, Gilles %A Roth, Camille %Z DOI : 10.1145/2914586.2914589 %< sans comité de lecture %( HT '16: Proceedings of the 27th ACM Conference on Hypertext and Social Media %B 27th ACM Conference on Hypertext and Social Media (HT 2016) %C Halifax, Nova Scotia, Canada %I ACM: Association for Computing Machinery %P 159 - 168 %8 2016-07-10 %D 2016 %R 10.1145/2914586.2914589 %K Collaboration %K Information Access %K Twitter %K Topic Mod-els %K Social Networks %Z Computer Science [cs]/Web %Z Computer Science [cs]/Social and Information Networks [cs.SI] %Z Computer Science [cs]/Document and Text Processing %Z Computer Science [cs]/Human-Computer Interaction [cs.HC] %Z Humanities and Social Sciences/SociologyConference papers %X 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. %G English %2 https://sciencespo.hal.science/hal-03597237/document %2 https://sciencespo.hal.science/hal-03597237/file/2016_Tamine_Social%20media-based%20collaborative%20information%20access.pdf %L hal-03597237 %U https://sciencespo.hal.science/hal-03597237 %~ SHS %~ SCIENCESPO %~ UPMC %~ UNIV-TLSE2 %~ UNIV-TLSE3 %~ CNRS %~ AO-SOCIOLOGIE %~ SOCIOLOGIE %~ SMS %~ LIP6 %~ UT1-CAPITOLE %~ CAMPUS-AAR %~ AAI %~ USPC %~ UPMC_POLE_1 %~ SORBONNE-UNIVERSITE %~ SU-SCIENCES %~ IRIT %~ IRIT-IRIS %~ IRIT-SMAC %~ SU-TI %~ IRIT-GD %~ IRIT-ICI %~ IRIT-UT1C %~ MEDIALAB %~ ALLIANCE-SU %~ SCPO_OA %~ TOULOUSE-INP %~ UNIV-UT3 %~ UT3-INP %~ UT3-TOULOUSEINP