HOME

= = Welcome to the Wiki of opinion mining!

Topics of opinion mining

 * 1) sentiment analysis
 * 2) topic modeling
 * 3) Text mining
 * 4) Word Cloud

**People**
[] [] [] ==
 * Bo Pang
 * Bing Liu

==

Tools of sentiment analysis
There are two tools to measure variations in the public mood. The first tool, OpinionFinder, analyses the text content of tweets submitted on a given day to provide a positive vs. negative daily time series of public mood. 1. **Opinion Finder** @http://www.cs.pitt.edu/mpqa/set_up_gate.html [] One good news of opinion finder, the 2.0 edition which is platform-free will be released soon. 2. **GPOMS** The second tool, GPOMS, it can generate a six-dimensional daily time series of public mood to provide a more detailed view of changes in public along 6 different mood dimensions, namely Calm, Alert, Sure, Vital, Kind and Happy. GPOMS’ mood dimensions and lexicon are derived from an existing and well-vetted psychometric instrument,namely the Profile of Mood States (POMS-bi).

"To make it applicable to Twitter mood analysis we expanded the original 72 terms of the POMS questionnaire to a lexicon of 964 associated terms by analyzing word co-occurrences in a collection of 2.5 billion 4- and 5-grams6 computed by Google in 2006 from approximately 1 trillion word tokens observed in publicly accessible Webpages [3,2]. The enlarged lexicon of 964 terms thus allows GPOMS to capture a much wider variety of naturally occurring mood terms in Tweets and map them to their respective POMS mood dimensions. We match the terms used in each tweet against this lexicon. Each tweet term that matches an n-gram term is mapped back."

[] [bad news, Johan Bollen no longer maitains this page, write to him] []

3. **LIWC** (Linguistic Inquiry and Word Count) To extract the sentiment of these tweets automatically, we used LIWC2007 (Linguistic Inquiry and Word Count; Pennebaker, Chung, and Ireland 2007), a text analysis software developed to assess emotional, cognitive, and structural components of text samples using a psychometrically validated internal dictionary. []

4. **LingPipe** In the paper of //The Pulse of News in Social Media: Forecasting Popularity//, the software of lingpipe was used. LingPipe is tool kit for processing text using computational linguistics.

[]

LingPipe is used to do tasks like:
 * Find the names of people, organizations or locations in news
 * __Automatically classify Twitter search results into categories__
 * Suggest correct spellings of queries

5. SentiWordNe [] SentiWordNet is a lexical resource for opinion mining. SentiWordNet assigns to each synset of WordNet three sentiment scores: positivity, negativity, objectivity.

6. WordNet

[|http://wordnet.princeton.edu/wordnet/download/current-version/#win]

7. R - tm.plugin.sentiment A brief introduction, click here.

8. Python (with package NLTK)

Summary of opinion mining studies
https://opinionmining.wikispaces.com/Blog

[] liubing's intro to opinion mining  Das & Chen, Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web, Management Science September 2007 vol. 53 no. 9 1375-1388.
 * References**