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Subjectivity Detection through Socio-Linguistic Features

Электронный научный архив УРФУ

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Поле Значение
 
Заглавие Subjectivity Detection through Socio-Linguistic Features
 
Автор Younus, Arjumand
Qureshi, M. Atif
Touheed, Nasir
 
Тематика SOCIAL SEARCH
SUBJECTIVITY
EMOTION-AWARE SEARCH
SOCIO-LINGUISTIC
 
Описание Social media platforms have opened new dimensions within the information retrieval
domain leading to a novel concept known as Social Information Retrieval. We argue that the concept of Social Information Retrieval can be extended by augmenting the huge amount of content on the traditional Web with the ever-growing rich Social Web content to increase the information richness of today’s search engines. This paper proposes a subjectivity detection
framework which can lead towards a proposed emotion-aware search engine interface. Our
proposed method differs from previous subjectivity analysis approaches in that it is the first method that takes into account social features of social media platforms for the subjectivity classification task. Through experimental evaluations, we observe the accuracy of the proposed method to be 86.21% which demonstrates a promising outcome for large-scale application of our
proposed subjectivity analysis technique.
 
Дата 2011-10-12T10:25:39Z
2011-10-12T10:25:39Z
2011
 
Тип Article
Journal article (info:eu-repo/semantics/article)
Published version (info:eu-repo/semantics/publishedVersion)
 
Идентификатор Younus Arjumand. Subjectivity Detection through Socio-Linguistic Features / Arjumand Younus, M. Atif Qureshi, Nasir Touheed // Web of Data: The joint RuSSIR/EDBT 2011 Summer School, August 15–19, 2011, Proceedings of the Fifth Russian Young Scientists Conference in Information Retrieval / B. Novikov, P. Braslavsky (Eds.). — St. Petersburg, 2011 — P. 55-62.
978-5-288-05225-5
http://elar.urfu.ru/handle/10995/3712
 
Язык en
 
Связанные ресурсы RuSSIR/EDBT2011
 
Формат 134739 bytes
application/pdf
 
Издатель St. Petersburg University Press