Linguistics and Languages

How analysis of mobile app reviews problematises linguistic approaches to internet troll detection

S. Monakhov

This study by Sergei Monakhov delves into the complexities of internet troll detection through linguistic analysis of over 180,000 app reviews. The findings highlight a 'troll coefficient' that mistakenly identifies genuine negative reviews as troll-like behavior, prompting a call for an improved prediction model to address this issue.

00:00

Playback language: English

Index

Abstract

This study investigates the challenges in using linguistic approaches for internet troll detection by analyzing over 180,000 app reviews. The research reveals that a "troll coefficient," previously effective in identifying trolls, also flags genuine negative reviews. This phenomenon is attributed to collaborative repatterning in online discussions where users adjust their language to avoid repetition, mimicking troll behavior. The study proposes a model to predict troll coefficients based on time intervals between reviews, suggesting that the previously successful algorithm needs refinement to account for this collaborative effect.

Publisher

HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS

Published On

Nov 18, 2021

Authors

Sergei Monakhov

Related Publications

Explore these studies to deepen your understanding of the subject.

Health and Fitness

Gender and academic year as moderators of the efficacy of mobile app interventions to promote physical activity in adolescents: a randomized controlled trial

A. Mateo-orcajada, R. Vaquero-cristóbal, et al.

Business

How to improve SME performance using iterative random forest in the empirical analysis of institutional complementarity

A. Sannabe

Linguistics and Languages

Linguistic borrowings in trade terminologies: an analysis of ancient Indian and Egyptian languages from 3300 BCE to 500 CE

P. Mohanan and N. Prakash

Medicine and Health

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

G. 2. D. Collaborators, D. Kanyin, et al.

Listen, Learn & Level Up

Over 10,000 hours of research content in 25+ fields, available in 12+ languages.

No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.

listen to research audio papers with researchbunny