DocumentCode
2967320
Title
Identifying focal patterns in social networks
Author
Sen, Fatih ; Wigand, R.T. ; Agarwal, Nishant ; Mahata, Debanjan ; Bisgin, H.
Author_Institution
Dept. of Inf. Sci., Univ. of Arkansas at Little Rock, Little Rock, AR, USA
fYear
2012
fDate
21-23 Nov. 2012
Firstpage
105
Lastpage
108
Abstract
Identifying authoritative individuals is a well-known approach in extracting actionable knowledge, known as “Knowledge Representation”, in a social network. Previous researches suggest measures to identify influential individuals, however, such individuals might not represent the appropriate context (relationships, interactions, etc.). For example, it is nearly an impossible task for a single individual to organize a mass protest of the scale of Occupy Wall Street. Similarly, other events such as the Arab Spring, coordinating crisis responses for natural disasters (e.g., the Haiti earthquake), or even organizing flash mobs would require a key set of individuals rather than a single or the most authoritative one. These events demonstrate the need and importance of examining influential structures rather than single individuals in social networks. A new methodology is proposed to identify such influential structures and recognizing their importance. The proposed methodology is evaluated empirically with real-world data from NIST´s Tweets2011 corpus. We also introduce a novel and objective evaluation strategy to ascertain the efficacy of the focal patterns. Challenges with future research directions are outlined.
Keywords
knowledge acquisition; knowledge representation; network theory (graphs); pattern clustering; social networking (online); text analysis; NIST´s Tweets2011 corpus; actionable knowledge extraction; authoritative individual identification; event analysis; focal pattern identification; influential structures; knowledge representation; real-world data; social networks; Blogs; Communities; Context; Data mining; Media; Twitter; event analysis; focal patterns; social media;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Aspects of Social Networks (CASoN), 2012 Fourth International Conference on
Conference_Location
Sao Carlos
Print_ISBN
978-1-4673-4793-8
Type
conf
DOI
10.1109/CASoN.2012.6412386
Filename
6412386
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