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Social Network Analysis and Mining

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01.03.2013 | Review Article

Opinion mining: reviewed from word to document level

verfasst von: Malik Muhammad Saad Missen, Mohand Boughanem, Guillaume Cabanac

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2013

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Abstract

Opinion mining is one of the most challenging tasks of the field of information retrieval. Research community has been publishing a number of articles on this topic but a significant increase in interest has been observed during the past decade especially after the launch of several online social networks. In this paper, we provide a very detailed overview of the related work of opinion mining. Following features of our review make it stand unique among the works of similar kind: (1) it presents a very different perspective of the opinion mining field by discussing the work on different granularity levels (like word, sentences, and document levels) which is very unique and much required, (2) discussion of the related work in terms of challenges of the field of opinion mining, (3) document level discussion of the related work gives an overview of opinion mining task in blogosphere, one of most popular online social network, and (4) highlights the importance of online social networks for opinion mining task and other related sub-tasks.

Vorheriger Artikel Enabling cross-site interactions in social networks

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Taken from slides of talk by Andrea Esuli on the topic of opinion mining in Istituto di Scienza e Tecnologie dell’Informazione Consiglio Nazionale delle Ricerche, Pisa, Italy, 14th June 2006.

A complete list of the General Inquirer categories is given at http://www.wjh.harvard.edu/inquirer/homecat.htm.

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Titel: Opinion mining: reviewed from word to document level
verfasst von: Malik Muhammad Saad Missen
Mohand Boughanem
Guillaume Cabanac
Publikationsdatum: 01.03.2013
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2013
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-012-0057-9

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