Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
The Journal of Machine Learning Research
Sentiment Mining in WebFountain
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Topic sentiment mixture: modeling facets and opinions in weblogs
Proceedings of the 16th international conference on World Wide Web
Red Opal: product-feature scoring from reviews
Proceedings of the 8th ACM conference on Electronic commerce
Opinion mining of customer feedback data on the web
Proceedings of the 2nd international conference on Ubiquitous information management and communication
Twitter power: Tweets as electronic word of mouth
Journal of the American Society for Information Science and Technology
Making the ordinary visible in microblogs
Personal and Ubiquitous Computing
Classifying sentiment in microblogs: is brevity an advantage?
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Comparing twitter and traditional media using topic models
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Design science in information systems research
MIS Quarterly
Classifying Consumer Comparison Opinions to Uncover Product Strengths and Weaknesses
International Journal of Intelligent Information Technologies
An Ontology Based Model for Document Clustering
International Journal of Intelligent Information Technologies
Effective Fuzzy Ontology Based Distributed Document Using Non-Dominated Ranked Genetic Algorithm
International Journal of Intelligent Information Technologies
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In Social Commerce customers evolve to be an important information source for companies. Customers use the communication platforms of Web 2.0, for example Twitter, in order to express their sentiments about products or discuss their experiences with them. These sentiments can be very important for the development of products or the enhancement of marketing strategies. The research goal is to analyze customer sentiments in Twitter. The first step in the research is the detection of topics in Twitter entries which contain patterns of interest. For the topic detection, the authors use Latent Dirichlet Allocation for topic modeling. The authors found event based topics in the exemplary context of Sony's 3D TV sets. In future work, the authors will implement sentiment analysis algorithms in order to determine sentiments in the entries corresponding to the detected topics.