SENTIRE 2016 - 6th Workshop on Sentiment Elicitation from Natural Text for Information Retrieval and Extraction

Sentiment Elicitation from Natural Text for Information Retrieval and Extraction (SENTIRE) is the IEEE ICDM workshop series on opinion mining. The term SENTIRE comes from the Latin feel and it is root of words such as sentiment and sensation. SENTIRE aims to provide an international forum for researchers in the field of opinion mining and sentiment analysis to share information on their latest investigations in social information retrieval and their applications both in academic research areas and industrial sectors. The broader context of the workshop comprehends Web mining, AI, Semantic Web, information retrieval and natural language processing.
? SENTIRE'16 (ICDM 2016, December 12th, Barcelona)
? SENTIRE'15 (ICDM 2015, November 14th, Atlantic City)
? SENTIRE'14 (ICDM 2014, December 14th, Shenzhen)
? SENTIRE'13 (ICDM 2013, December 7th, Dallas)
? SENTIRE'12 (ICDM 2012, December 10th, Brussels)
? SENTIRE'11 (ICDM 2011, December 11th, Vancouver)
RATIONALE
Memory and data capacities double approximately every two years and, apparently, the Web is following the same rule. User-generated contents, in particular, are an ever-growing source of opinion and sentiments which are continuously spread worldwide through blogs, wikis, fora, chats and social networks. The distillation of knowledge from such sources is a key factor for applications in fields such as commerce, tourism, education and health, but the quantity and the nature of the contents they generate make it a very difficult task. Due to such challenging research problems and wide variety of practical applications, opinion mining and sentiment analysis have become very active research areas in the last decade.
Our understanding and knowledge of the problem and its solution are still limited as natural language understanding techniques are still pretty weak. Most of current research in sentiment analysis, in fact, merely relies on machine learning algorithms. Such algorithms, despite most of them being very effective, produce no human understandable results such that we know little about how and why output values are obtained. All such approaches, moreover, rely on syntactical structure of text, which is far from the way the human mind processes natural language. Next-generation opinion mining systems should employ techniques capable to better grasp the conceptual rules that govern sentiment and the clues that can convey these concepts from realization to verbalization in the human mind.
TOPICS
SENTIRE aims to provide an international forum for researchers in the field of opinion mining and sentiment analysis to share information on their latest investigations in social information retrieval and their applications both in academic research areas and industrial sectors. The broader context of the workshop comprehends Web mining, AI, Semantic Web, information retrieval and natural language processing. Topics of interest include but are not limited to:
? Sentiment identification & classification
? Opinion and sentiment summarization & visualization
? Explicit & latent semantic analysis for sentiment mining
? Concept-level opinion and sentiment analysis
? Sentic computing
? Opinion and sentiment search & retrieval
? Time evolving opinion & sentiment analysis
? Semantic multidimensional scaling for sentiment analysis
? Multidomain & cross-domain evaluation
? Domain adaptation for sentiment classification
? Multimodal sentiment analysis
? Multimodal fusion for continuous interpretation of semantics
? Multilingual sentiment analysis & re-use of knowledge bases
? Knowledge base construction & integration with opinion analysis
? Transfer learning of opinion & sentiment with knowledge bases
? Sentiment corpora & annotation
? Affective knowledge acquisition for sentiment analysis
? Biologically inspired opinion mining
? Sentiment topic detection & trend discovery
? Big social data analysis
? Social ranking
? Social network analysis
? Social media marketing
? Comparative opinion analysis
? Opinion spam detection