Conversation retrieval for microblogging sites

Matteo Magnani; Danilo Montesi; Luca Rossi

doi:10.1007/s10791-012-9189-9

Conversation retrieval for microblogging sites

Matteo Magnani, Danilo Montesi, Luca Rossi

Aalborg Universitet

Publikation: Artikel i tidsskrift og konference artikel i tidsskrift › Tidsskriftartikel › Forskning › peer review

Abstract

In this article we introduce a novel search paradigm for microblogging sites resulting from the intersection of Information Retrieval and Social Network Analysis (SNA). This approach is based on a formal model of on-line conversations and a set of ranking measures including SNA centrality metrics, time-related conversational metrics and other specific features of current microblogging sites. The ranking approach has been compared to other methods and tested on two well known social network sites (Twitter and Friendfeed) showing that the inclusion of SNA metrics in the ranking function and the usage of a model of conversation can improve the results of search tasks.

Originalsprog	Engelsk
Tidsskrift	Information Retrieval
Vol/bind	15
Udgave nummer	3-4
Sider (fra-til)	354-372
Antal sider	19
ISSN	1386-4564
DOI	https://doi.org/10.1007/s10791-012-9189-9
Status	Udgivet - 1 feb. 2013

Emneord

Conversation retrieval
Social network sites
Social media
Monitoring
Social network analysis metrics

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10.1007/s10791-012-9189-9

http://www.springerlink.com/index/10.1007/s10791-012-9189-9

Citationsformater

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AU - Montesi, Danilo

AU - Rossi, Luca

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N2 - In this article we introduce a novel search paradigm for microblogging sites resulting from the intersection of Information Retrieval and Social Network Analysis (SNA). This approach is based on a formal model of on-line conversations and a set of ranking measures including SNA centrality metrics, time-related conversational metrics and other specific features of current microblogging sites. The ranking approach has been compared to other methods and tested on two well known social network sites (Twitter and Friendfeed) showing that the inclusion of SNA metrics in the ranking function and the usage of a model of conversation can improve the results of search tasks.

AB - In this article we introduce a novel search paradigm for microblogging sites resulting from the intersection of Information Retrieval and Social Network Analysis (SNA). This approach is based on a formal model of on-line conversations and a set of ranking measures including SNA centrality metrics, time-related conversational metrics and other specific features of current microblogging sites. The ranking approach has been compared to other methods and tested on two well known social network sites (Twitter and Friendfeed) showing that the inclusion of SNA metrics in the ranking function and the usage of a model of conversation can improve the results of search tasks.

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KW - Social network sites

KW - Social media

KW - Monitoring

KW - Social network analysis metrics

KW - Conversation retrieval

KW - Social network sites

KW - Social media

KW - Monitoring

KW - Social network analysis metrics

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JO - Information Retrieval

JF - Information Retrieval

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Conversation retrieval for microblogging sites

Abstract

Emneord

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