Mennatallah El-Assady is a research fellow at the ETH AI Center, prior to that she was a research associate in the group for Data Analysis and Visualization at the University of Konstanz (Germany) and in the Visualization for Information Analysis lab at the University of Ontario Institute of Technology (Canada). She works at the intersection of data analysis, visualization, computational linguistics, and explainable artificial intelligence. Her general research interest is in combining data mining and machine learning techniques with visual analytics, specifically for text data. In particular, she is researching methods of the automatic analysis and visualization of transcribed verbatim text corpora. She has gained experience working in close collaboration with political science and linguistic scholars over several years, which lead to the development of the http://lingvis.io/ platform. More recently, she has been working on establishing the explainable AI framework http://explainer.ai/. El-Assady has co-founded and co-organized several workshop series, notably, http://vis4dh.org/, http://visxai.io/, and http://argvis-workshop.lingvis.io/.
Verbatim text transcripts capture the rapid exchange of opinions, arguments, and information among participants of a conversation. As a form of communication that is based on social interaction, multiparty conversations are characterized by an incremental development of their content structure. In contrast to highly-edited text data (e.g., literary, scientific, and technical publications), verbatim text transcripts contain non-standard lexical items and syntactic patterns. Thus, analyzing these transcripts automatically introduces multiple challenges.