Posted by Ajay Tejwani | Posted in Social Media | Posted on 25-08-2010
Who wouldn’t like to get influential on Twitter? But, having most followers means you have the most influence? NO, says a recent HP Labs study. The study suggests that most Twitter users are passive and the Twitter users with the most influence are those who retweet. Here are also some FAQs on the study.
According to the research, it is important to separate the concept of “influence” from “popularity.” While a user on Twitter may have a large number of followers, his or her influence is more strongly associated with their engagement with the network, rather than the total number of followers or retweets. To identify Twitter influencers, the authors devised an algorithm called the IP Algorithm. This algorithm assigns a relative influence score and passivity score to every user:
- “Influence” depends on both the quantity and quality of the user’s audience
- “Passivity” is a measure of how difficult it is for other users to influence him or her
The algorithm makes the following assumptions:
- Influence score depends on the number of people the user influences as well as their passivity.
- Influence score depends on how dedicated the people the user influences are. Dedication is measured by the amount of attention a user pays to a given one as compared to everyone else.
- A user’s passivity score depends on the influence of those who he’s exposed to but not influenced by.
- A user’s passivity score depends on how much he rejects other user’s influence compared to everyone else.
2.5 million users were included in the dataset show that the influence measure is a good predictor of URL clicks, outperforming several other measures .
The study concludes: “This study shows that the correlation between popularity and influence is weaker than it might be expected. This is a reflection of the fact that for information to propagate in a network, individuals need to forward it to the other members, thus having to actively engage rather than passively read it and cease to act on it.” The authors also see their measure of influence applicable to other social networks.