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