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TREC 06 : Finding opinionated posts, either positive or negative, about a query

Modeling Influence Opinions and Structure in Social Media. Akshay Java Advisor: Tim Finin. Thesis Statement. Modeling Influence.

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TREC 06 : Finding opinionated posts, either positive or negative, about a query

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  1. Modeling Influence Opinions and Structure in Social Media Akshay Java Advisor: Tim Finin Thesis Statement Modeling Influence An accurate model of influence on the Blogosphere must analyze and combine many contributing factors, including topic, social structure, opinions, biases and time. We will develop, implement and experimentally evaluate such a model to demonstrate its improved accuracy over models based on any of these factors.’’ • Epidemic Based Influence Models • Linear Threshold Model • Σ bwv ≥ θv • w is the active neighbor of v, • θv intrinsic threshold for a node • Greedy Heuristic • Assign random θv • Compute approx influenced set • At each step, add the node that increases the marginal gain in the size of the influenced set • Limitations • Selected nodes may belong to different topics • Social structure not considered • Static View of the network • Extended Model • Finds influential nodes for a topic • Models opinions, bias and trust • Identifies communities and social impact • Tracks temporal evolution of a meme • Richer framework to model influence Influence is Topical Opinions and Bias Influence Readers Popular Topics in Feeds That Matter • TREC 06: • Finding opinionated posts, • either positive or negative, • about a query • 2006 TREC Blog corpus: • 80K blogs, 300K post • 50 test queries • BlogVox opinion extraction system • Document and sentence level scorers • Combined scores using an SVM • meta-learner • Data cleaning: splogs and post identification Tech Slashdot Gizmodo Wired Bias towards MSM sources Politics Dems Reps “Topic Ontology” derived from 83K user feed subscriptions consisting of 500K feeds. Provides a readership-based metric for influence. Dailykos Talkingpoints Michellemalkin RightwingNews Temporal Trends Indicate Influence Ongoing Research Who started talking about the topic first? Who were the early adopters? Who were the influencers? Who was the source of the information? What are the future trends to watch out for? A generalized framework for influence in Social Media Predictive Models for topical trends and influence Link Polarity and Trust Improved sentiment analysis Generative Models for the Blogosphere

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