Identifying Argumentative Questions in Web Search Logs

authored by

Yamen Ajjour, Pavel Braslavski, Alexander Bondarenko, Benno Stein

Abstract

We present an approach to identify argumentative questions among web search queries. Argumentative questions ask for reasons to support a certain stance on a controversial topic, such as ''Should marijuana be legalized?'' Controversial topics entail opposing stances, and hence can be supported or opposed by various arguments. Argumentative questions pose a challenge for search engines since they should be answered with both pro and con arguments in order to not bias a user toward a certain stance. To further analyze the problem, we sampled questions about 19 controversial topics from a large Yandex search log and let human annotators label them as one of factual, method, or argumentative. The result is a collection of 39,340 labeled questions, 28% of which are argumentative, demonstrating the need to develop dedicated systems for this type of questions. A comparative analysis of the three question types shows that asking for reasons and predictions are among the most important features of argumentative questions. To demonstrate the feasibility of the classification task, we developed a BERT-based classifier to map questions to the question types, reaching a promising macro-averaged F>sub>1-score of 0.78.

External Organisation(s)

Leipzig University
Bauhaus-Universität Weimar

Type

Conference contribution

Pages

2393-2399

No. of pages

7

Publication date

07.07.2022

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Software, Information Systems, Computer Graphics and Computer-Aided Design

Electronic version(s)

https://doi.org/10.1145/3477495.3531864 (Access: Closed)