Make Fake News Visible

In recent years, the issue of influencing people by disseminating false information has been a recurrent topic in the media. For example, the US presidential election in 2016 sparked a broad debate about the influence of Russian bots in social media. Furthermore Donald Trump, who popular- ized the term "Fake News" , is also a considerable source of misinformation himself (Sweden [4], Inauguration [1] etc). The consequences of such Fake News are not only reflected in election results but can also have other effects, For example, the claim made in 2013 by the "Syrian Electronic Army" about a terrorist attack on the White House in which President Obama was injured, caused a crash on the stock markets. Meanwhile, in WhatsApp had to deactivate the group share function, as it caused lynchings of innocent people in India. When fast spreading misinformation has severe real-world consequences, we speak of "Digital Wildfires". We have created the UMOD [5] project, which aims at understanding such Digital Wildfires on all forms of electronic news platforms. The work described here moves within the scope of social networks, especially Twitter.

We are interested in questions concerning the visualization of social networks, primarily the following two:

  1. Visualization of particularly large graphs.
  2. Interactive Visualization.

For the visualization of particularly large graphs, there are a handful of tricks that can be used to merge groups of nodes, for example. In addition, there is a huge number of layout algorithms that arrange a graph in a way that makes it look particularly beautiful. Here force-directed graph algorithms [3] should be evaluated and implemented.
Another topic we consider in this context are distributed implementations of these algorithms. since the social networks we deal with are often too large to process on a single machine.
Beyond that we look for solutions to visualize special scenarios. As an example, consider the two visualizations in Figure 3.
The purpose of this proposal is simply to give you a guideline, a concrete plan for your work, we would make according to your interests and ideas. Please send us an email if you are interested.


Supervision
This thesis is offered by Simula Research Laboratory in cooperation with the University of Oslo (UIO). We are most of the time at Simula in Fornebu where you also have a place to work. The supervision will be taken over by Johannes Langguth and Prof. Carsten Griwodz.


Offer
At Simula we offer exciting work in close cooperation with leading research groups as well as excel- lent working conditions. We provide a stimulating work environment and the opportunity to build future networks. Simula strives to achieve a balance between genders, and women are particularly encouraged to apply.


Expectations
We expect self-motivation, initiative and the ability to work independently, as well as working knowledge of a programming language such as Python or Java. Knowledge of social network analysis is not required, although familiarity with Twitter would be helpful.

Publisert 3. apr. 2019 07:45 - Sist endret 3. apr. 2019 07:59

Omfang (studiepoeng)

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