Twitter Research

In Twitter we have the situation that the network between users is multiplex (people can hold numerous ties with each other): Users can either a) follow each other b) interact with each other or c) retweet each other. The three types of ties, manifest themselves in three different networks that can be sort of laid … Continue reading →

A few months ago I’ve made a blog post (https://twitterresearcher.wordpress.com/2012/01/17/the-strength-of-ties-revisited/)  investigating tie strenghts on Twitter and their influence on  retweets. Well it turns out  that my analysis was lacking a lot of detail, so I re-did it again considering more aspects than before. So lets get started. Data The data that I am using for … Continue reading →

In this blog post I want to talk about how to find people on Twitter that are interested in the “same things”. I have posted a number on entries about How to create an ontology of user’s interests (https://twitterresearcher.wordpress.com/2012/04/16/5/ and https://twitterresearcher.wordpress.com/2012/03/16/a-net-of-words-a-high-level-ontology-for-twitter-tags/) How to scrape off the seed users representing those interests from wefollow (https://twitterresearcher.wordpress.com/2012/02/17/how-to-make-sense-out-of-twitter-tags/) which is a … Continue reading →

Is it that in a group the more stronger ties the group has, also more information gets diffused between its members? Well according to Granovetter saying that information among people with strong ties tends to diffuse faster this should be the case.  But if we want to study this phenomenon in Twitter we have to … Continue reading →

Motivation A very interesting blog post from the people at socialflow was the inspiration for this little study. The socialflow study analyzed the Twitter outlets of the main news providers like CNN, NYT to find out if they have a common audience, how they compare when it comes to being retweeted an so on. So I thought … Continue reading →

I’ve been blogging about the idea that people form networks based on their interests for a while now.  As you maybe remember we used to use the tags on wefollow to find out what people are interested in on Twitter. And in the  last post I have shown how to create a post-hoc ontology  from tags … Continue reading →

Knowing that people form networks in twitter based on their interest I have investigated the tags that are listed on wefollow (see below) below. Motivation: Since those tags are rather chaotic and in no particular order except that they are listed by the number of followers I was thinking how do others organise those interests. … Continue reading →

We all know the problem although there seems to be an “interest based” community out there, we honestly don’t know how to start to “tap” in into these communities. A first way is to see what is out there by looking at Twitter directories such as wefollow.com or twellow.com What you might notice that when … Continue reading →

Some of you have seen the very interesting article from the Facebook Data team about the echo chamber of social networks. The slate magazine has a nice review of this recent bakshy and adamic paper. They come to an illustrative conclusion if you had 100 weak ties and 10 strong ties: “The amount of information spread due … Continue reading →

Introduction We have all heard about the importance of so called opinion leaders, mavens, influencers or simply central people. I have covered in a recent article in my blog. Using the same approach in this blog article I will try to find out how  much such opinion-leadership differs across different communities and which factors predict … Continue reading →

Motivation I was recently analyzing Twitter networks and started to create groups according to a certain topic. An example would be the 100 most relevant people for the keyword “snowboarding”. Based on using the Twitter list feature where you can tag people with the word snowboarding the more often people are tagged the more they … Continue reading →

Some of you have probably read the very popular article on techcrunch on “The rise of interest based social network” such as pintrest, instagram, thumb, foodspotting and so on. While it seems like this is a new phenomenon I think that this kind of interest based social networks has existed for a long time in … Continue reading →