www2011 conference - posters

This is my third post on www2011 conference. The first and second covers the conference and papers. This one covers the posters.

Posters

Text Sentiment Analysis using Stop Words uses a very innovative approach of using the stop words and gaps between them to analyze the sentiment of the text. This is completely opposite of what most text processing/information extraction algorithms do where they ignore the stop words. A nice out of the box thinking idea.

Evaluation of Valuable UGC in Social News websites analyzes the value of UGC to social news websites. It finds that current news and events gets lot more value from UGC than technology news.

Hierarchical Organization of Unstructured Consumer Reviews tries to organize consumer reviews into hierarchy of aspects for a product (iphone -> software, speaker, battery..) of what consumers liked/disliked.

ReadAlong: Reading Articles and Comments Together uses bag of words and topic models (extracted using LDA) to group comments to parts of the article they belong to (typically comments is attached to complete article - while they comment might be about a part of the article). This is a joint work of yahoo and IISc.

Web Information Extraction using Markov Logic Networks proposes the use of MLN for general purpose extraction of structured information from web sites. They demonstrate this for specific domains (like Restaurants, Books etc). This is a joint work of yahoo, IISc and Microsoft.

Detecting Group Review Spam targets a very specific problem of review spam done by group of people (as opposed to spam by individuals). They identify group of individuals and find out whether the patterns the follow together indicates a abnormal uniform group behavior based on set of features.

Classification Based Framework for Concept Summarization is another work from yahoo. This groups images into a concept using a classification based framework and uses LDA to get category information.

Spammer Networks in Twitter analyzes the collaborative strategies used by group of spammers in twitter to avoid detection and increase reach. Repeated URLs in recent tweets were used to initially identify set of suspected spammers. The spammers gets legitimate users following them by follow-backs and also follow each other. An interesting analysis of the patterns of spammers.