Applications and Challenges of Sentiment and Stance Analysis

Dr. Petra Kralj Novak | December 9, 2019 | 16:00 | S.2.42

Abstract:

Social media are computer-based technologies that provide means of information and idea sharing, as well as entertainment and engagement handly available as mobile applications and websites to both private users and businesses.  As social media communication is mostly informal, it is an ideal environment for the use of emoji and for detecting the population’s sentiments and stance. Sentiment* and stance** analysis have been heavily researched in the last decade and the technology to address these data analysis tasks have developed rapidly. In this talk, several inspiring sentiment and stance analysis applications will be presented, varying in data source, topics, language, and approaches used. As a result of several years of experience in sentiment and stance analysis, best practices guidelines will be provided and remaining challenges exposed.
*Sentiment analysis is the field of study that analyzes people’s opinions, sentiments, evaluations, attitudes, and emotions from a text.
**Stance analysis is the task of automatically determining from text whether the author of the text is in favor of, against, or neutral towards a proposition or target.

CV:

Dr. Petra Kralj Novak is a researcher at the Department of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, Slovenia. Her research belongs to the wide area of knowledge discovery from databases. Currently, as a postdoctoral researcher, she analyses social and mainstream media focusing on the mediated sentiment and hate speech. Avant-garde research in analyzing the role of emojis in conveying sentiment was published in P. Kralj Novak, et al. „Sentiment of emojis“ and is the main reference for current research in the analysis of emoji. Dr. Kralj Novak publishes research papers and datasets in top academic venues. Her thesis focused on rule induction from class labeled data, where the induced rules are intended for human interpretation. The main findings of the thesis are published in Journal of Machine Learning Research and in the Encyclopedia of Machine Learning. She also designed and implemented GMOtreck – a system for optimization of laboratory level traceability of genetically modified organisms. Dr. Kralj Novak regularly serves in scientific programs of major academic and industrial conferences such as ICDM, ICML, DS, IDA, and Southern Data Science. She is PC chair of the  22nd International Conference on Discovery Science (2019, Split Croatia). From 2006 to 2009, and from 2018 on she is secretary and treasurer of SLAIS – the Slovenian Artificial Intelligence Society. She has also actively collaborated in several national and European research projects. She is the coordinator of the EU REC AG project IMSyPP: Innovative Monitoring Systems and Prevention Policies of Online Hate Speech (2020-2022).

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