Social Media-Based Collaborative Information Access: Analysis of Online Crisis-Related Twitter Conversations
Lynda Tamine
(1, 2)
,
Laure Soulier
(1, 3)
,
Lamjed Ben Jabeur
(1, 2)
,
Frédéric Amblard
(1, 4)
,
Chihab Hanachi
(5, 4)
,
Gilles Hubert
(1, 2)
,
Camille Roth
(6, 7)
1
IRIT-IRIS -
Recherche d’Information et Synthèse d’Information
2 UT3 - Université Toulouse III - Paul Sabatier
3 MLIA - Machine Learning and Information Access
4 UT Capitole - Université Toulouse Capitole
5 IRIT-SMAC - Systèmes Multi-Agents Coopératifs
6 médialab - médialab (Sciences Po)
7 CMB - Centre Marc Bloch
2 UT3 - Université Toulouse III - Paul Sabatier
3 MLIA - Machine Learning and Information Access
4 UT Capitole - Université Toulouse Capitole
5 IRIT-SMAC - Systèmes Multi-Agents Coopératifs
6 médialab - médialab (Sciences Po)
7 CMB - Centre Marc Bloch
Lynda Tamine
- Fonction : Auteur
- PersonId : 744669
- IdHAL : lynda-tamine-lechani
- ORCID : 0000-0002-3615-8032
- IdRef : 110204875
Laure Soulier
- Fonction : Auteur
- PersonId : 8070
- IdHAL : soulierl
- ORCID : 0000-0001-9827-7400
- IdRef : 189293683
Lamjed Ben Jabeur
- Fonction : Auteur
- PersonId : 935223
Frédéric Amblard
- Fonction : Auteur
- PersonId : 10741
- IdHAL : frederic-amblard
- ORCID : 0000-0002-2653-0857
- IdRef : 077629450
Chihab Hanachi
- Fonction : Auteur
- PersonId : 980773
- IdRef : 155258354
Gilles Hubert
- Fonction : Auteur
- PersonId : 737483
- IdHAL : ghubert
- ORCID : 0000-0003-3494-7561
- IdRef : 22364109X
Camille Roth
- Fonction : Auteur
- PersonId : 1042429
- IdHAL : camille-roth
- ORCID : 0000-0003-3925-7957
Résumé
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.
Domaines
Web Web Réseaux sociaux et d'information [cs.SI] Réseaux sociaux et d'information [cs.SI] Traitement du texte et du document Traitement du texte et du document Interface homme-machine [cs.HC] Interface homme-machine [cs.HC] Sociologie SociologieFormat du dépôt | Fichier |
---|---|
Type de dépôt | Communication dans un congrès |
Titre |
en
Social Media-Based Collaborative Information Access: Analysis of Online Crisis-Related Twitter Conversations
|
Résumé |
en
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.
|
Auteur(s) |
Lynda Tamine
1, 2
, Laure Soulier
1, 3
, Lamjed Ben Jabeur
1, 2
, Frédéric Amblard
1, 4
, Chihab Hanachi
5, 4
, Gilles Hubert
1, 2
, Camille Roth
6, 7
1
IRIT-IRIS -
Recherche d’Information et Synthèse d’Information
( 1001827 )
- IRIT
118 Route de Narbonne
31062 Toulouse Cedex 9
- France
2
UT3 -
Université Toulouse III - Paul Sabatier
( 217752 )
- 118 route de Narbonne - 31062 Toulouse
- France
3
MLIA -
Machine Learning and Information Access
( 408311 )
- France
4
UT Capitole -
Université Toulouse Capitole
( 81148 )
- 2 rue du Doyen-Gabriel-Marty - 31042 Toulouse Cedex 9
- France
5
IRIT-SMAC -
Systèmes Multi-Agents Coopératifs
( 396069 )
- IRIT
118 Route de Narbonne
31062 Toulouse Cedex 9
- France
6
médialab -
médialab (Sciences Po)
( 394361 )
- 27 rue Saint-Guillaume - 75337 Paris Cedex 07
- France
7
CMB -
Centre Marc Bloch
( 84774 )
- Friedrichstr. 191 D-10117 Berlin
- Allemagne
|
Langue du document |
Anglais
|
Date de production/écriture |
2016-07-10
|
Vulgarisation |
Non
|
Comité de lecture |
Non
|
Invité |
Non
|
Audience |
Non spécifiée
|
Actes |
Oui
|
Date de publication |
2016-07-10
|
Page/Identifiant |
159 - 168
|
Date début congrès |
2016-07-10
|
Ville |
Halifax, Nova Scotia
|
Pays |
Canada
|
Commentaire |
DOI : 10.1145/2914586.2914589
|
Source |
HT '16: Proceedings of the 27th ACM Conference on Hypertext and Social Media
|
Date fin congrès |
2016-07-13
|
Titre du congrès |
27th ACM Conference on Hypertext and Social Media (HT 2016)
|
URL du congrès ou éditeur |
https://ht.acm.org/ht2016/
|
Licence |
Paternité - Pas d'utilisation commerciale - Partage selon les Conditions Initiales
|
Domaine(s) |
|
Éditeur commercial |
|
Organisateur du congrès |
|
Voir aussi |
|
Mots-clés |
en
Collaboration, Information Access, Twitter, Topic Mod-els, Social Networks
|
DOI | 10.1145/2914586.2914589 |
Spire (Sciences Po) | 2441/6bei5rgsa195cb3uvde4954l2q |
Fichier principal
2016_Tamine_Social media-based collaborative information access.pdf ( 1.82 Mo
)
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