Wenbo Wang @ Kno.e.sis Center Resume

I am a Ph.D student at Kno.e.sis Center and I am working with Professor Amit Sheth. My broad research interests include: Text Mining, Natural Language Processing and Social Media analytics. My current focus is on Emotion Identification, Sentiment Analysis and Intention Mining.

Research Experience

• Sentiment/Emotion Analysis

• Understanding and Modeling Emotions with Tweets (2011.11-present) (demo)

  There is nothing more exciting than embracing the era of big data. Aim to study people's emotions at the level of millions of data entries. Collect, analyze, model emotions in social media and eventually predict people's emotions by the texts people write. Here are some preliminary but interesting discoveries on Twitter users from Estern Standard Timezone (US & Canada) between Nov. 10th and Nov. 28th:
  • The most significant (more than 65%) emotion on Nov. 24th is thankfulness . (of course^_^) diagram link
  • The most significant emotion after people get up is thankfulness (see the peak between 7am and 9am); The most significant emotion at night is love (see the love/affection peak around 10pm). diagram link

• Unsupervised Sentiment Clue Extraction in Social Media (2011.6-present)

  Besides single words, phrases can also convey interesting sentiments. For example, "must see" and "rate 5 starts" in movie reviews. Extract target-dependent word and phrase clues as well as corresponding polarities from tweets by applying an optimization model to minimize the inconsistency relations among sentiment clues.

• Discover Fine-grained Emotions in Suicide Note (2011.6-2011.9)

  Suicide takes away over 98 lives each day in US [stats]. The first step towards preventing people from committing suicide is to identify and track people's emotions. Constructed a hybrid classifier that is able to discover the sentence-level emotions from 16 categories, e.g., love, pride, abuse, anger, happiness, guilt, etc. Explored a variety of lexical, syntactic and knowledge-based features. Proposed an algorithm to automatically extract effective syntactic and lexical patterns from training examples.

• Social Media Analytics

• Social Media Based Election Prediction with Different User Groups (March 2012 - present)

  Characterize social media users into different groups in the dimensions of engagement degree, tweet mode, content type and political preference. Then analyze and examine the predictive power of different user groups in the context of 2012 U.S. Republican Presidential Primaries.

• Twitris+: 360° Social Media Analysis (2011.6-present)

  Twitris+ is a Semantic Web application that facilitates understanding of social perceptions by Semantics-based processing of massive amounts of event-centric data:
  • Sentiment/Emotion analysis demo for 2012 U.S. Election
  • Sentiment analysis demo for Occupy Wall Street

• Data Integration and Object Disambiguation using MapReduce

• Internship in WOO (A Web Of Objects) Team @ Yahoo! (2010.6-2011.4)

  The goal of WOO project is to integrate existing high quality knowledge bases, such as DBpedia, Yahoo! Movies, etc. and come with an integrated WOO knowledge base. My job is to disambiguate and integrate movie, actor and director objects in DBpedia and Yahoo! Movies. My contributions include:
  • Designed and implemented object disambiguation algorithm in Hadoop environment
  • Generic features as well as domain/problem specific features

• Pattern based Synonym/Antonym Extraction

• Human Performance Cognition Ontology(HPCO) (2008.9-2010.6)

  The ultimate goal of HPCO is to better perform knowledge discovery by semantic search and browsing. Focused domain hierarchy is semi-automatically constructed from Wikipedia and triples are extracted from scientific literatures (PubMed). My job is to align predicates in extracted triples with existing predicates in domain ontology and the idea is to automatically discover verb relationships like, synonym/antonym, from seed verb synonyms/antonyms. My contributions include:
  • Extracted a restricted set of seed synonym/antonym verbs from Wordnet
  • Constructed probability enabled synonym/antonym patterns from POS tagged training corpus
  • Applied learned patterns to obtain more synonym/antonym verbs

Publications

• Lu Chen, Wenbo Wang, Amit P. Sheth. Are Twitter Users Equal in Predicting Elections? A Study of User Groups in Predicting 2012 U.S. Republican Presidential Primaries. In Proceedings of the Fourth International Conference on Social Informatics (SocInfo'12) 2012
• Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth. Harnessing Twitter ‘Big Data’ for Automatic Emotion Identification. 2012 ASE International Conference on Social Computing (SocialCom 2012), (demo, dataset download )
• Alan Smith, Amit Sheth, Ashutosh Jadhav, Hemant Purohit, Lu Chen, Michael Cooney, Pavan Kapanipathi, Pramod Anantharam, Pramod Koneru and Wenbo Wang. Twitris+: Social Media Analytics Platform for Effective Coordination. NSF SoCS Symposium, 2012
• Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth. Extracting Diverse Sentiment Expressions with Target-dependent Polarity from Twitter. In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM), 2012, (Accpetancerate: 20%)
• Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth. Discovering Fine-grained Sentiment in Suicide Notes. Biomedical Informatics Insights, 2012
• Ramakanth Kavuluru, Christopher Thomas, Amit Sheth, Victor Chan, Wenbo Wang, Alan Smith, “An Up-to-date Knowledge-Based Literature Search and Exploration Framework for Focused Bioscience Domains, IHI 2012 - 2nd ACM SIGHIT Intl Health Informatics Symposium, January 28-30, 2012.
• Wenbo Wang, Christopher Thomas, Amit Sheth, Victor Chan. Pattern-Based Synonym and Antonym Extraction. 48th ACM Southeast Conference, ACMSE2010, Oxford Mississippi, April 15-17, 2010
• Christopher J. Thomas, Wenbo Wang, Pankaj Mehra, Delroy Cameron, Pablo N. Mendes, and Amit P. Sheth.. What Goes Around Comes Around – Improving Linked Opend Data through On-Demand Model Creation. In: Proceedings of the WebSci10: Extending the Frontiers of Society On-Line, April 26-27th, 2010, Raleigh, NC: US.
• Ashutosh Jadhav, Wenbo Wang, Raghava Mutharaju, Pramod Anantharam, Vinh Nyugen, Amit P. Sheth, Karthik Gomadam, Meenakshi Nagarajan, and Ajith Ranabahu, Twitris: Socially Influenced Browsing, Semantic Web Challenge 2009, demo at 8th International Semantic Web Conference, Oct. 25-29 2009, Washington, DC, USA

Education

• 2008-present PhD student in Computer Science Department at Wright State University (GPA: 4.0) Advisor: Professor Amit Sheth


• 2005.9-2008.4 Master student in School of Computer Science and Technology at Beijing University of Posts and Telecommunications (BUPT), China. Advisor: Professor Xiaofeng Li


• 2001.9-2005.6 Bachelor student in School of Information Science and Engineering at Central South University (CSU), China. Advisor: Professor Jun Peng

Computer Skills

• Programming Languages: Java, C, Scheme, PHP, XML, HTML, SQL, Pig
• Web Technologies: RDF, OWL, SPARQL, XML, HTML, Hadoop, Storm
• Operating Systems: Windows, Linux/Unix