EveOut: an event-centric news dataset to analyze an outlet's event selection patterns

Authors

  • Swati Swati Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia
  • Dunja Mladenić Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia
  • Tomaž Erjavec Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

DOI:

https://doi.org/10.31449/inf.v45i7.3410

Abstract

Automation of computational models to study the structure of events and their value to news outlets is an effective way to understand event-outlet relationships. However, the scarcity of publicly available, comprehensive event-centric news datasets restricts the implementation of such models. To overcome this bottleneck, we collected seventeen months of event data using Event Registry to generate EveOut, a publicly available event-centric news dataset. To conduct statistical analysis, we first select five English-language and three in Slovenian-language news outlets. We then retrieved all the events covered by them and used it to document the prevalence of geographical, temporal, categorical, and several other aspects of the event selection bias by these outlets. We illustrate the significance of our dataset in the field of digital humanities by identifying a motivating use case. The dataset is publicly available from the dedicated website http://cleopatra.ijs.si/EveOut/, which provides a detailed description of the fields, usage information, and a link to the GitHub repository.

Author Biographies

Swati Swati, Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

Researcher,Artificial Intelligence Lab,Department of Information and Communication Technologies

Dunja Mladenić, Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

Professor,Artificial Intelligence Lab,Department of Information and Communication Technologies

Tomaž Erjavec, Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

Professor,Department of Knowledge Technologies

References

Dylan Bourgeois, J ́er ́emie Rappaz, and Karl Aberer. 2018. Selection bias in news coverage: learning it, fighting it. In Companion Proceedings of The Web Conference2018. International World Wide Web Conferences Steering Committee, 535–543.

Cindy Cheng, Joan Barcel ́o, Allison Spencer Hartnett, Robert Kubinec, and Luca Messerschmidt. 2020. Covid-19 government response event dataset (coronanet v. 1.0). Nature Human Behaviour, 1–13.

Tomaˇz Erjavec and Dunja Mladeni ́c. 2020. Eveout: reproducible event dataset for studying and analyzing the complex event-outlet relationship.

Felix Hamborg, Norman Meuschke, and BelaGipp. 2018. Bias-aware news analysis using matrix-based news aggregation.International Journal on Digital Libraries, 1–19.

Gregor Leban, Blaˇz Fortuna, Janez Brank,and Marko Grobelnik. 2014. Event registry: learning about world events from news. In Proceedings of the 23rd International Conference on World Wide Web, 107–110.

Kalev Leetaru and Philip A Schrodt. 2013. Gdelt: global data on events, location, and tone, 1979–2012. In ISA annual convention, 1–49.

Philip A Schrodt, Om ̈ur Yilmaz, DeborahJ Gerner, and Dennis Hermreck. 2008. The cameo (conflict and mediation event observations) actor coding framework. In2008 Annual Meeting of the International Studies Association.

Stuart N Soroka. 2016. Gatekeeping and the negativity bias. In Oxford Research Encyclopedia of Politics.

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Published

2021-12-31

How to Cite

Swati, S., Mladenić, D., & Erjavec, T. (2021). EveOut: an event-centric news dataset to analyze an outlet’s event selection patterns. Informatica, 45(7). https://doi.org/10.31449/inf.v45i7.3410