CRANK: A hybrid model for user and content sentiment classification using social context and community detection

Sánchez Rada, Juan Fernando and Iglesias Fernandez, Carlos Ángel (2020). CRANK: A hybrid model for user and content sentiment classification using social context and community detection. "Applied Sciences-Basel", v. 10 (n. 1662); pp. 1-22. ISSN 2076-3417. https://doi.org/10.3390/app10051662.

Description

Title: CRANK: A hybrid model for user and content sentiment classification using social context and community detection
Author/s:
  • Sánchez Rada, Juan Fernando
  • Iglesias Fernandez, Carlos Ángel
Item Type: Article
Título de Revista/Publicación: Applied Sciences-Basel
Date: 1 March 2020
ISSN: 2076-3417
Volume: 10
Subjects:
Freetext Keywords: sentiment analysis; social context; social network analysis; online social networks
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Recent works have shown that sentiment analysis on social media can be improved by fusing text with social context information. Social context is information such as relationships between users and interactions of users with content. Although existing works have already exploited the networked structure of social context by using graphical models or techniques such as label propagation, more advanced techniques from social network analysis remain unexplored. Our hypothesis is that these techniques can help reveal underlying features that could help with the analysis. In this work, we present a sentiment classification model (CRANK) that leverages community partitions to improve both user and content classification. We evaluated this model one xisting datasets and compared it to other approaches.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2015-68284-RSEMOLAUnspecifiedUnspecified
Horizon 2020740934TRIVALENTUNIVERSITA DEGLI STUDI ROMA TRETerrorism pReventIon Via rAdicaLisation countEr-NarraTive
Horizon 2020644632MixedEmotionsNATIONAL UNIVERSITY OF IRELAND GALWAYSocial Semantic Emotion Analysis for Innovative Multilingual Big Data Analytics Markets

More information

Item ID: 63860
DC Identifier: http://oa.upm.es/63860/
OAI Identifier: oai:oa.upm.es:63860
DOI: 10.3390/app10051662
Official URL: https://www.mdpi.com/2076-3417/10/5/1662
Deposited by: Memoria Investigacion
Deposited on: 29 Sep 2020 14:50
Last Modified: 29 Sep 2020 14:50
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