In the age of misinformation, fact-checking and post-truth, misperception has become too dangerously common. In this regards, several recent political events such as Brexit in Europe and 2016 presidential election in US have even highlighted the importance of mis- and disinformation detection more and more. One of the most important topic in this area is identification of social bots and fake news speaders. Discovering social bots from Twitter and accordingly analysis of its results including posts tweeted by such bots would significantly improve identification of fake news as well. This has been discussed repeatedly as one of the important research priorities of web science in social media networks, news agencies, and governments.
In this regard, this research lab concentrates more in details in the existing methods of fact checking, innovations that may enrich current manual and human-based methods and artificial intelligence supporting the social bots identification methods. There has been some scholar reseach and scientific methods in this regard. We will use state-of-the-art literature to provide the novel approach. The first goal is to understand the state-of-the-art in this area, deepen studies in machine learning algorithms and employ those in automation of fact checking and misinformation discovery from the web. The work should be started by the identification of best-fit datasets to the use-case scenarios. In this regard and in best case, all developed solutions of different student groups may be packed as plugins, software suit or a web service available to the public. Potential scientific publications is foreseen as one of outcomes of each research group. Further details of this lab will be discussed with students in the introductory and kick-off meetings.
The first meeting in which we present the content and aim of this lab will be on Thursday, 29.03.2018 at 12:00 PM in room E 428.
The kickoff meeting was on Thursday 29.03.2018 at 12:00 PM.
We will organize the Projektpraktikum together with the Forschungspraktikum. Bachelor students will focus on software engineering tasks, while master students will work on research-oriented tasks. The students will work in teams and are encouraged to use agile methodologies (e.g. Scrum) and collaborative software development technology (e.g. GitHub). The use of project management software tools (e.g. Redmine) is recommended. The lab documentation will be handled through Google Drive. In order to have an access to the lab documentation drive, you will need a registration through email.
If you are interested in participating, please send an email to Dr. Mahdi Bohlouli (firstname.lastname@example.org). Registration in KLIPS (https://klips.uni-koblenz-landau.de/v/102136 or https://klips.uni-koblenz-landau.de/v/102133) is mandatory after forming the final groups.