TY - CHAP

T1 - Hate Speech in Perception Management Campaigns: New Opportunities of Sentiment Analysis and Affective Computing

AU - Колотаев, Юрий Юрьевич

N1 - Kolotaev Y.Y. Hate Speech in Perception Management Campaigns: New Opportunities of Sentiment Analysis and Affective Computing // The Palgrave Handbook of Malicious Use of AI and Psychological Security / ed. E. Pashentsev. – Cham: Palgrave Macmillan, 2023. – P. 105–132.

PY - 2023

Y1 - 2023

N2 - This chapter examines the malicious use of artificial intelligence (MUAI) in the dissemination of hate speech on social media. The focus of this chapter is emotion-driven artificial intelligence (AI), and, therefore, attention is devoted mainly to affective computing and sentiment analysis. Affective computing as a research field and technological domain enables the recognition and simulation of human emotions in various inputs. Sentiment analysis is a method that entails the use of machine learning to recognize emotional and subjective meanings. Both approaches are applied to identify hate speech on social media. Yet, even though there are many positive consequences (e.g., automatic detection of misinformation and harmful content), the further development of AI might also become instrumental in perception management campaigns targeted at a particular audience. This chapter aims to identify a general scenario for the MUAI in the spread of hate speech, estimate the interdependence of social and technical factors of such scenario, and specify possible solutions to combat this threat. To this end, the chapter is based on scenario analysis and includes an assessment of existing examples, risks, and counteractions related to the threat of MUAI in the dissemination of hate speech.

AB - This chapter examines the malicious use of artificial intelligence (MUAI) in the dissemination of hate speech on social media. The focus of this chapter is emotion-driven artificial intelligence (AI), and, therefore, attention is devoted mainly to affective computing and sentiment analysis. Affective computing as a research field and technological domain enables the recognition and simulation of human emotions in various inputs. Sentiment analysis is a method that entails the use of machine learning to recognize emotional and subjective meanings. Both approaches are applied to identify hate speech on social media. Yet, even though there are many positive consequences (e.g., automatic detection of misinformation and harmful content), the further development of AI might also become instrumental in perception management campaigns targeted at a particular audience. This chapter aims to identify a general scenario for the MUAI in the spread of hate speech, estimate the interdependence of social and technical factors of such scenario, and specify possible solutions to combat this threat. To this end, the chapter is based on scenario analysis and includes an assessment of existing examples, risks, and counteractions related to the threat of MUAI in the dissemination of hate speech.

KW - Affective computing

KW - Artificial intelligence

KW - Hate speech

KW - Perception management

KW - Sentiment analysis

UR - https://www.mendeley.com/catalogue/aac7ad45-4683-3390-a09b-97d5a55c5356/

U2 - 10.1007/978-3-031-22552-9_5

DO - 10.1007/978-3-031-22552-9_5

M3 - Chapter

SN - 9783031225529

SP - 105

EP - 132

BT - The Palgrave Handbook of Malicious Use of AI and Psychological Security

A2 - Pashentsev, Evgeny

PB - Palgrave Macmillan Ltd.

ER -