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Showing posts from August, 2010

Emotions Draw Close Friends: Analyzing the Social Network Structure of Facebook Fan Pages

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Recently we were wondering if the social network structure of fans of a brand, a star, or a cause tells us how passionate the fans are. To be more precise, we were looking at the network structure of the friendship network of Facebook fan pages. This means that we collected – as far a publicly accessible – the friendship network of the people who clicked on the “like” button on a fan page. For a start, look at the fan page of our own COINs2010 conference (by the way, the conference will be soon in Savannah Oct 7 to 9, at SCAD, we hope to see many of you there ☺ ). The dark dots in the network are the fans of COINs2010, the green dots are their friends. This means that for this initial analysis we looked at how many and how well-connected friends a fan of COINs2010 has. We ignored direct links between the fans, but focused on their external friendship network. In this first attempt we looked at a total of 15 fan groups in 5 categories, see the table below: We (admittedly subjectively

Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”

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We have been working on trying to predict market indicators for quite some time by analyzing Web Buzz , predicting who will win an Oscar, or how well movies do at the box office . Among other things we have correlated posts about a stock on Yahoo Finance and Motley’s Fool with the actual stock price, predicting the closing price of the stock on the next day based on what people say today on Yahoo Finance, on the Web and Blogs about a stock title. The rising popularity of twitter gives us a new great way of capturing the collective mind up to the last minute. In our current project we analyze the positive and negative mood of the masses on twitter, comparing it with broad stock market indices such as Dow Jones, S&P 500, and NASDAQ. We collected the twitter feeds from one whitelisted IP for six months from March 30, 2009 to Sept 4, 2009, ranging from 5680 to 42820 tweets per day. According to twitter this corresponds to a randomized subsample of about one hundredth of the full volum