Understanding change in social media networks.
Tackling the problem of negative dynamics in social media.
Understanding online/offline spillover effects.
Developing methods for the analysis of large-scale text data.
Applying statistical methods for the analysis of large-scale social media text data.
Local Chair Organizing Team, 2020 Sunbelt Virtual Conference, International Network for Social Network Analysis.
EPJ Data Science
ACM Web Science Conference 2020
EDML (2020) Evaluation and Experimental Design in Data Mining and Machine Learning
ASONAM (2020) Advances in Social Network Analysis and Mining
Social media serves as a place to gather information, interact, and form opinions. More recently, online firestorms, fake news and hate speech have shaken our beliefs and hopes about the positive power of social media to their very foundations. While negative emotions are in the core of human behavior, algorithms on social media, enhanced by Artificial Intelligence (AI) can produce and reinforce new dynamics.
In this project, we will address the mathematical modeling of the formation and dynamics of opinions in large groups of interacting people on social media. Our primary objective is to understand the driving factors of social media group level phenomena that lead to negative dynamics and to offer approaches on how to detect, react to, and possibly mitigate these dynamics early on. The fundamental goal is to reveal the possible relationship between the simple “social forces” acting at individual level, being the “first principles” of social interaction or the game rules, and the potential emergence of a global behavior.
The results of our study will provide insights of ethical relevance by discussing responsibility, delegation and control mechanisms in human-AI interacting systems.
This project analyzes the previously unexplored questions of whether people’s online behavior spills over to their behavior in the offline world and what mediates the respective effects.
Employing a two-stage experimental setup, we first use field experiments on social media for online manipulations of our study participants. Second, we study the potential spillovers to our participants’ offline behavior in a laboratory setting. Specifically, we investigate whether attention from others on social media leads to a polarization of people’s political opinions and erodes their commitment to truth. We hypothesize that the treatment group receiving a relatively high levels of attention on social media will show more polarized profiles of political opinions.
The anonymization of qualitative interview data is of high importance. For the purpose of secondary use of data, anonymized data is essential. While automated processes in anonymization tasks are becoming more and more common, we provide a tool that keeps researcher in control of their data. Automated decisions give all-in-one solutions, but studying qualitative interview data depends on the needs of every single researcher. We provide a tool that enables researcher to make individual decisions with the information needed, on the level required. In this report, we propose a solution to anonymize qualitative interview data with the purpose to create own coding schemes and individual abstraction levels. We built a tool that assists in working with textual interview data. By using the tool, processes can be optimized and important information can be obtained at the same time.
The project seeks to extend its diachronic perspective towards the seventeenth century and, at the same time, to shift its focus onto a dialectics of pluralisation and the positioning of new authorities that is observable not only in the field of poetic theory, but especially in the interaction of theory and poetic practice. This is of particular importance as in the course of the sixteenth century, love poetry is affected by new pluralizing tendencies brought about by the discovery of new models, both practical (the genre of the ode) and theoretical (Aristotle, Longinus).
It is the aim of this project to demonstrate how in the situation described, on the one hand, order is re-imposed by introducing new hierarchical structures and more and more complex systems and, on the other hand, conflicts are avoided by ascribing new meanings to canonical texts and by obscuring contradictions both in theory and lyrical practice. New efforts at establishing order often create an apparent but superficial order which, thus, harbours the potential for further pluralisation. In the wake of Aristotelianism, there is a new tendency towards the elaboration of a poetological system that no longer uses a single author as its sole model but integrates model authors such as Petrarch as exemplifications of a set of rules existing independently (Tasso) or even has to discard them as inappropriate (Tassoni, Marino).
It will be a long-term aim of the project to integrate its findings into the larger attempt to draw up an archaeology of the seemingly unified, but highly heterogeneous concept of ‘lyric poetry’ which can first be discerned in certain publications just before and after 1600 (e.g. Marino, La Lira) and which remains problematic even today.