OpinionCloud

(for YouTube)

• Synopsis
• Firefox Add-on
• Project Outline
• People
• Related Publications

Install the OpinionCloud Firefox add-on, or the Google Chrome extension.

Sentiment Analysis & Opinion Visualization. In sentiment analysis a word's polarity can be identified by measuring its co-occurrence with words whose polarity is known in advance, i.e., if a given word occurs with a high probability in the vicinity of positive (negative) words it can be considered positive (negative) as well. Neutral words, however, tend to occur arbitrarily next to words of both polarities. We use this idea to train a dictionary of opinion words which also contains slang terms that are often used in comments. The dictionary is then used to classify the words of comments into positive, negative, and neutral words. By default, words that are not contained in the dictionary are considered neutral.

The visualization of the opinions found in a set of comments is done as shown in Figure 1. The words are arranged in a cloud where the color of a word denotes its polarity and the size of a word its frequency in the comments. This visualization is comparable to the well-known tag clouds for folksonomies.

Why YouTube? We have chosen YouTube as a working example for our technology since a comment on YouTube usually contains only some kind of opinion exclamation, and, a large amount of comments is available. For a user, reading these comments is time-consuming and boring, or put another way, comments on YouTube are neither universally accessible nor useful. Just kidding! ;-) However, for an information retrieval researcher these comments form a unique large-scale corpus of highly opinion-coloured language. For instance, to train our dictionary we have analyzed about 9 million YouTube comments.

• Martin Potthast
• Steffen Becker