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Do Violent People Smile: Social Media Analysis of their Profile Pictures

Authors:

Claudio Lucchese,

Salvatore OrlandoAuthors Info & Claims

WWW '18: Companion Proceedings of the The Web Conference 2018

Pages 1465 - 1468

https://doi.org/10.1145/3184558.3191594

Published: 23 April 2018 Publication History

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Abstract

The popularity of online social platforms has also determined the emergence of violent and abusive behaviors reflecting real life issues into the digital arena. Cyberbullying, Internet banging, pedopornography, sexting are examples of these behaviors, as witnessed in the social media environments. Several studies have shown how to approximately detect those behaviors by analyzing the social interactions and in particular the content of the exchanged messages. The features considered in the models basically include detection of o ensive language through NLP techniques and vocabularies, social network structural measures and, if available, user context information. Our goal is to investigate those users who adopt offensive language and hate speech in Twitter by analyzing their profile pictures. Results show that violent people smile less and they are dominating by anger, fear and sadness.

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Cited By

Gautam VMaheshwari HTiwari RAgarwal ATrivedi N(2024)Federated Learning Empowered Violence Recognition in CCTV Footage: A YOLO and ResNet-50 Fusion Approach2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467832(01-06)Online publication date: 4-Jan-2024
https://doi.org/10.1109/IDCIoT59759.2024.10467832
Bhalodia SVekariya V(2023)Violence activity detection techniques – A reviewMACHINE LEARNING AND INFORMATION PROCESSING: PROCEEDINGS OF ICMLIP 202310.1063/5.0168382(060027)Online publication date: 2023
https://doi.org/10.1063/5.0168382
Jain MBhanodia PSethi K(2023)Artificial Intelligent Model for Riot and Violence Detection that Largely Affect Societal Health and Local Healthcare SystemIndustry 4.0 and Healthcare10.1007/978-981-99-1949-9_6(113-131)Online publication date: 2-Dec-2023
https://doi.org/10.1007/978-981-99-1949-9_6
Show More Cited By

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Do Violent People Smile: Social Media Analysis of their Profile Pictures

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Published In

cover image ACM Other conferences

WWW '18: Companion Proceedings of the The Web Conference 2018

April 2018

2023 pages

ISBN:9781450356404

General Chairs:
Pierre-Antoine Champin
Université Claude Bernard Lyon 1, France
,
Fabien Gandon
Inria, Université Côte d'Azur, CNRS, I3S, France
,
Lionel Médini
Université Claude Bernard Lyon 1, CNRS, LIRIS, France
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Panagiotis G. Ipeirotis
New York University, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 23 April 2018

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WWW '18

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IW3C2

WWW '18: The Web Conference 2018

April 23 - 27, 2018

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Gautam VMaheshwari HTiwari RAgarwal ATrivedi N(2024)Federated Learning Empowered Violence Recognition in CCTV Footage: A YOLO and ResNet-50 Fusion Approach2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467832(01-06)Online publication date: 4-Jan-2024
https://doi.org/10.1109/IDCIoT59759.2024.10467832
Bhalodia SVekariya V(2023)Violence activity detection techniques – A reviewMACHINE LEARNING AND INFORMATION PROCESSING: PROCEEDINGS OF ICMLIP 202310.1063/5.0168382(060027)Online publication date: 2023
https://doi.org/10.1063/5.0168382
Jain MBhanodia PSethi K(2023)Artificial Intelligent Model for Riot and Violence Detection that Largely Affect Societal Health and Local Healthcare SystemIndustry 4.0 and Healthcare10.1007/978-981-99-1949-9_6(113-131)Online publication date: 2-Dec-2023
https://doi.org/10.1007/978-981-99-1949-9_6
Ramzan MAbid AKhan HAwan SIsmail AAhmed MIlyas MMahmood A(2019)A Review on State-of-the-Art Violence Detection TechniquesIEEE Access10.1109/ACCESS.2019.29321147(107560-107575)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2932114
Kumar ASachdeva N(2019)Cyberbullying detection on social multimedia using soft computing techniques: a meta-analysisMultimedia Tools and Applications10.1007/s11042-019-7234-z78:17(23973-24010)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s11042-019-7234-z

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