Literatur |
Überblick Opinion Mining/Sentiment Analyse: Mohammad Sadegh , Roliana Ibrahim, Zulaiha Ali Othman, Opinion Mining and Sentiment Analysis: A Survey, International Journal of Computers & Technology, Volume 2 No. 3, June, 2012.
Informationen über soziale Beziehungen nutzen: Xia Hu, Lei Tang, Jiliang Tang, Huan Liu, Exploiting Social Relations for Sentiment Analysis in Microblogging, WSDM ’13, February 4–8, 2013, Rome, Italy.
Semantische Features nutzen: Hassan Saif, Yulan He and Harith Alani, Semantic Sentiment Analysis of Twitter, In: The 11th International Semantic Web Conference (ISWC 2012), 11-15 November 2012, Boston, MA, USA.
Kontrastives Opinion Modeling: Yi Fang, Luo Si, Naveen Somasundaram, Zhengtao Yu, Mining Contrastive Opinions on Political Texts using Cross-Perspective Topic Model, WSDM’12, February 8–12, 2012, Seattle, Washingtion, USA.
Ontologie-basierte Sentiment Analyse: Matteo Baldoni, Cristina Baroglio, Viviana Patti and Paolo Rena, From Tags to Emotions: Ontology-driven Sentiment Analysis in the Social Semantic Web, Journal of Intelligenza Artificiale, 6(1):41-54, 2012.
Gemeinsame Sentiment-Topic Erkennung: Chenghua Lin, Yulan He, Richard Everson and Stefan Rüger, Weakly-supervised Joint Sentiment-Topic Detection from Text, IEEE Transactions on Knowledge and Data Engineering (Volume:24 , Issue: 6), 2012.
Data Sparsity mindern: Hassan Saif, Yulan He, Harith Alani, Alleviating Data Sparsity for Twitter Sentiment Analysis, MSM2012 - 2nd Workshop on Making Sense of Microposts, MSM2012, April 16, 2012, Lyon, France.
Einfluss anderer Faktoren: Onur Kucuktunc, B. Barla Cambazoglu, Ingmar Weber, Hakan Ferhatosmanoglu, A Large-Scale Sentiment Analysis for Yahoo! Answers, WSDM’12, February 8–12, 2012, Seattle, Washington, USA. |