Determining Filter Bubbles in Twitter


Abgeschlossene Masterarbeit


  • Ali Sahan


  • AI Master
  • Ability to read and understand papers written in English.
  • Ability to perform academic writing.
  • Strong programming skills (e.g.Java, essential)
  • Lectures Information Retrieval oder Information Mining and the use of tools such as RapidMiner (essential)


In the last decade, social media have become the platforms par excellence for all kinds of online information exchange, such as: content creation, consumption and sharing; commenting on and engaging with contents posted by others; organisation of events; reporting and tracking of real world events; rating and reviewing products; catching up with the latest developments in the news; etc. Among the best known platforms today are Facebook, Twitter, Sina Weibo, Reddit and Instagram. Besides individuals, the presence of companies, agencies, institutions and politicians has also increased in social media. One of their objectives is to engage with a broader audience, while also learning from them. For instance, companies are interested in finding out what customers think about their products to further improve their services and perform targeted advertisements. Given the scale of social media use, it is also being leveraged to perform predictions on a variety of issues such as political elections, referenda and stock markets.

While social media mining and analysis has become the ultimate approach to dig for knowledge and understand opinions of others it is only available for those who are technically equipped. For instance researchers from social sciences or other less technical studies have difficulties to perform social media mining and analysis and are excluded from the knowledge available in social media.

Currently we are developing a web application that addresses this gap. The application allows users to login and create their own analyses pipelines. Each analysis process consists of building blocks that can be easily plugged in to a pipeline. A user is able to create several pipelines. The heard of each pipeline consist of analysis solutions. For instance, one solution would be the analysis of sentiment of social media posts, another would be the prediction of political bias, etc.

Among various analysis solutions determining filter bubbles is another approach how to look at social media. A filter bubble is defined for example by a set of persons, who are connected in social media. A connection can be a direct communication or common interests in the social network. The investigation in filter bubbles has potential usefulness to find people who have similar interests and understand the aspects that brought them together. The aspects could be for instance similar interests in some political party or direction, belief, opinion on a certain topic, brand, theory, an action that is under plan, event planning, help offering or seeking, etc.

The aim of this master thesis is to develop an analysis solution that aims to determine filter bubbles. The candidate should develop the solution to be used within the web application. In addition, the candidate should investigate various ways of presentations of filter bubbles to the user. Also the determination of aspects (i.e. why did this group came together) should be investigated.