Hello, my name is Tatiana Sennikova. I graduated from the Faculty of Information Technologies and Computer Engineering of Volga State University of Technology in 2010. During my study I was working as a programmer in the Multimedia System Laboratory of the University. After the graduation, I shifted my focus towards internet marketing and data analysis.

Between 2010 and 2014 I was working as a marketing specialist in different internet startups in Moscow. I was working with projects such as: bookmate (international electronic library with more than 5,000,0000 readers) and zvooq (leading music streaming service in Russia and CIS). I worked in consulting with companies such as: Aeroflot (the largest airline in Russia), Kayak, Agoda, E5 (the online project of Russia’s largest food retail group), BinBabk, and Moscow Credit Bank.

In 2014-2016 I was improving my data science qualification by obtaining a Master’s degree in Web Sciences in the University of Koblenz-Landau. At the same time I worked as a research assistant in the Data Science department of the GESIS – Leibniz-Institute for the Social Sciences in Cologne.


I conducted research at the GESIS – Leibniz-Institut for the Social Sciences as a data analyst. I collected and analyzed online data from Twitter, Facebook, Google Trends, and Wikipedia. I performed text mining, applied machine learning techniques, and performed time series analysis of online data.

Here are some projects I was participating in:

Wikiwhere: An Interactive Tool for Studying the Geographical Provenance of Wikipedia References

Me and my colleges Martin Körner, Florian Windhäuser, Claudia Wagner, and Fabian Flöck developed a tool that helps to study the geographical bias of Wikipedia articles in different language editions. During this research we applied machine learning techniques over data collected from DBpedia. The accuracy of our method exceed the prediction based only on IP adress by 20%. This research was presented on the CSS Winter Symphosium in 2016 with a poster. Further, a number magazines wrote about this project:

Attention Dynamics of Scientists on the Web

In my master’s thesis, I analyzed the online attention towards scientists and their research topics. The studies compared the attention dynamics towards the winners of important scientific prizes with scientists who did not receive a prize. For this, time series analysis techniques were applied over the data collected on the Web. The research was inspired by the works of Eamon Keogh  in time series analysis. This work was presented on the General Online Research conference as a finalist in the master’s thesis contest.


CSS Winter Synphosium in 2016: Wikiwhere: An Interactive Tool for Studying the Geographical Provenance of Wikipedia References

ICWSM 2016: Cultural Relation Mining on Wikipedia

General Online Reearch 2017: Attention Dynamics of Scientists on the Web p. 63-64