Towards Better Understanding Researcher Strategies in Cross-Lingual Event Analytics

TL;DR

This paper investigates researchers' strategies in analyzing multilingual event data, highlighting factors influencing their choices and offering recommendations to improve cross-lingual event analytics tools.

Contribution

It presents an analysis of researcher strategies in cross-lingual event analytics based on case studies, revealing influencing factors and current limitations.

Findings

Researchers adapt content, method, and feature selection strategies based on event and language factors.

The study identifies key influence factors affecting research strategies.

Recommendations for supporting researchers in cross-lingual event analytics are provided.

Abstract

With an increasing amount of information on globally important events, there is a growing demand for efficient analytics of multilingual event-centric information. Such analytics is particularly challenging due to the large amount of content, the event dynamics and the language barrier. Although memory institutions increasingly collect event-centric Web content in different languages, very little is known about the strategies of researchers who conduct analytics of such content. In this paper we present researchers' strategies for the content, method and feature selection in the context of cross-lingual event-centric analytics observed in two case studies on multilingual Wikipedia. We discuss the influence factors for these strategies, the findings enabled by the adopted methods along with the current limitations and provide recommendations for services supporting researchers in cross-lingual event-centric analytics.