Appel: ICDM workshop series on opinion mining

Thierry Hamon hamon at LIMSI.FR
Fri Jul 25 19:47:54 UTC 2014


Date: Wed, 23 Jul 2014 01:50:27 -0500 (EST)
From: SenticNet <feeds at sentic.net>
Message-ID: <222240518.1350768.1406098227974.open-xchange at bosoxweb05.eigbox.net>
X-url: http://sentic.net/sentire


Apologies for cross-posting,

Submissions are invited for the 4th edition of Sentiment Elicitation
from Natural Text for Information Retrieval and Extraction (SENTIRE),
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. The workshop is going to be held in Shenzhen on 14th
December 2014. For more information, please visit:
http://sentic.net/sentire

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 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

TIMEFRAME
- August 1st, 2014: Submission deadline
- September 26th, 2014: Notification of acceptance
- October 20th, 2014: Final manuscripts due
- December 14th, 2014: Workshop date

SUBMISSIONS AND PROCEEDINGS
Authors are required to follow IEEE Computer Society Press Proceedings
Author Guidelines. The paper length is limited to 10 pages, including
references, diagrams, and appendices, if any. Manuscripts are to be
submitted through EasyChair. Each submitted paper will be evaluated by
three PC members with respect to its novelty, significance, technical
soundness, presentation, and experiments. Accepted papers will be
published in IEEE ICDM proceedings.  Selected, expanded versions of
papers presented at the workshop will be invited to a forthcoming
Special Issue of Cognitive Computation on opinion mining and sentiment
analysis.

ORGANIZERS
- Erik Cambria, Nanyang Technological University (Singapore)
- Bing Liu, University of Illinois at Chicago (USA)
- Yunqing Xia, Tsinghua University (China)
- Yongzheng Zhang, LinkedIn Inc. (USA)



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