LINGUIST List 22.5118 Mon Dec 19 2011 Calls: Computational Linguistics/ IEEE Intelligent Systems (Jrnl) Editor for this issue: Brent Miller <brentlinguistlist.org> LINGUIST is pleased to announce the launch of an exciting new feature: Easy Abstracts! Easy Abs is a free abstract submission and review facility designed to help conference organizers and reviewers accept and process abstracts online. Just go to: http://www.linguistlist.org/confcustom, and begin your conference customization process today! With Easy Abstracts, submission and review will be as easy as 1-2-3! Directory         1.     Bjoern Schuller , IEEE Intelligent Systems Message 1: IEEE Intelligent Systems Date: 19-Dec-2011 From: Bjoern Schuller <schullertum.de> Subject: IEEE Intelligent Systems E-mail this message to a friend Full Title: IEEE Intelligent Systems Call Deadline: 01-Jul-2012 Special Issue of IEEE Intelligent Systems Magazine Concept-Level Opinion and Sentiment Analysis Submission deadline: 1 July 2012 http://www.computer.org/portal/web/computingnow/iscfp2 Opinions play a primary role in decision-making processes. Whenever people need to make a choice, they are naturally inclined to hear others' opinions. In particular, when the decision involves consuming valuable resources, such as time and/or money, people strongly rely on their peers' past experiences. Just a few years ago, the main sources for collecting such information were friends, acquaintances and, in some cases, specialized magazines or websites. The passage from a read-only to a read-write Web has provided people with new tools that allow them to create and share, in a timely and cost-efficient way, their own contents, ideas, and opinions with virtually millions of people connected to the World Wide Web. The opportunity to capture the opinions of the general public about social events, political movements, company strategies, marketing campaigns, and product preferences has raised more and more interest both in the scientific community, for the exciting emergent challenges, and in the business world, for the remarkable fallouts in marketing and financial market prediction. Mining opinions and sentiments from natural language, however, is an extremely difficult task: it involves a deep understanding of most of the explicit and implicit, regular and irregular, syntactical and semantic rules of a language. Existing approaches mainly rely on parts of text in which opinions and sentiments are explicitly expressed such as polarity terms, affect words, and their co-occurrence frequencies. However, opinions and sentiments are often conveyed implicitly through latent semantics, which make purely syntactical approaches ineffective. In this light, this special issue focuses on the introduction, presentation, and discussion of novel approaches to opinion mining and sentiment analysis that are not entirely based on domain-dependent corpora but also on general- purpose semantic knowledge bases. The main motivation for the issue, in particular, is to go beyond a mere word-level analysis of text and provide novel concept-level approaches to opinion mining and sentiment analysis that allow a more efficient passage from (unstructured) textual information to (structured) machine-processible data, in potentially any domain. Articles are thus invited in areas such as AI, the Semantic Web, knowledge- based systems, and adaptive and transfer learning for research on opinion and sentiment retrieval and analysis. Potential topics include * Opinion and sentiment summarization and visualization * Explicit and latent semantic analysis for opinion and sentiment mining * Knowledge base construction and integration with opinion and sentiment analysis * Transfer learning of opinion and sentiment with knowledge bases * Time-evolving opinion and sentiment analysis * Corpora and resources for opinion and sentiment analysis * Multimodal sentiment analysis * Multidomain and cross-domain evaluation * Multilingual sentiment analysis and reuse of knowledge bases Guest Editors: Erik Cambria, National University of Singapore, Singapore; cambrianus.edu.sg Björn Schuller, Technische Universität München, Germany; schullertum.de Bing Liu, University of Illinois at Chicago, USA; liubcs.uic.edu Haixun Wang, Microsoft Research Asia, China; haixun.wangmicrosoft.com Catherine Havasi, MIT Media Laboratory, USA; havasimedia.mit.edu Read more issues|LINGUIST home page|Top of issue Page Updated: 19-Dec-2011       About LINGUIST    |   Contact Us       While the LINGUIST List makes every effort to ensure the linguistic relevance of sites listed on its pages, it cannot vouch for their contents.