Next Article in Journal
Data Exchange in Cluster Structure for Longevity of IoT
Next Article in Special Issue
LPWAN Technologies: Emerging Application Characteristics, Requirements, and Design Considerations
Previous Article in Journal
Intelligent Thermal Comfort Controlling System for Buildings Based on IoT and AI
Previous Article in Special Issue
A Survey of Security Vulnerability Analysis, Discovery, Detection, and Mitigation on IoT Devices
Review

A Survey on Troll Detection

Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
*
Author to whom correspondence should be addressed.
Future Internet 2020, 12(2), 31; https://doi.org/10.3390/fi12020031
Received: 17 January 2020 / Revised: 7 February 2020 / Accepted: 7 February 2020 / Published: 10 February 2020
(This article belongs to the Collection Featured Reviews of Future Internet Research)
A troll is usually defined as somebody who provokes and offends people to make them angry, who wants to dominate any discussion or who tries to manipulate people’s opinions. The problems caused by such persons have increased with the diffusion of social media. Therefore, on the one hand, press bodies and magazines have begun to address the issue and to write articles about the phenomenon and its related problems while, on the other hand, universities and research centres have begun to study the features characterizing trolls and to look for solutions for their identification. This survey aims at introducing the main researches dedicated to the description of trolls and to the study and experimentation of methods for their detection. View Full-Text
Keywords: troll detection; antisocial behaviour; social media troll detection; antisocial behaviour; social media
MDPI and ACS Style

Tomaiuolo, M.; Lombardo, G.; Mordonini, M.; Cagnoni, S.; Poggi, A. A Survey on Troll Detection. Future Internet 2020, 12, 31. https://doi.org/10.3390/fi12020031

AMA Style

Tomaiuolo M, Lombardo G, Mordonini M, Cagnoni S, Poggi A. A Survey on Troll Detection. Future Internet. 2020; 12(2):31. https://doi.org/10.3390/fi12020031

Chicago/Turabian Style

Tomaiuolo, Michele; Lombardo, Gianfranco; Mordonini, Monica; Cagnoni, Stefano; Poggi, Agostino. 2020. "A Survey on Troll Detection" Future Internet 12, no. 2: 31. https://doi.org/10.3390/fi12020031

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop