Discovery and Analysis of Evolving Topical Social Discussions on Unstructured Microblogs View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Kanika Narang , Seema Nagar , Sameep Mehta , L. V. Subramaniam , Kuntal Dey

ABSTRACT

Social networks have emerged as hubs of user generated content. Online social conversations can be used to retrieve users interests towards given topics and trends. Microblogging platforms like Twitter are primary examples of social networks with significant volumes of topical message exchanges between users. However, unlike traditional online discussion forums, blogs and social networking sites, explicit discussion threads are absent from microblogging networks like Twitter. This inherent absence of any conversation framework makes it challenging to distinguish conversations from mere topical interests. In this work, we explore semantic, social and temporal relationships of topical clusters formed in Twitter to identify conversations. We devise an algorithm comprising of a sequence of steps such as text clustering, topical similarity detection using TF-IDF and Wordnet, and intersecting social, semantic and temporal graphs to discover social conversations around topics. We further qualitatively show the presence of social localization of discussion threads. Our results suggest that discussion threads evolve significantly over social networks on Twitter. Our algorithm to find social discussion threads can be used for settings such as social information spreading applications and information diffusion analyses on microblog networks. More... »

PAGES

545-556

References to SciGraph publications

Book

TITLE

Advances in Information Retrieval

ISBN

978-3-642-36972-8
978-3-642-36973-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-36973-5_46

DOI

http://dx.doi.org/10.1007/978-3-642-36973-5_46

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029725884


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