TY - JOUR
T1 - An analysis of people's reasoning for sharing real and fake news
AU - Shrestha, Anu
AU - Spezzano, Francesca
N1 - Publisher Copyright:
© 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Presented at the MISINFO 2021 Workshop, held in conjunction with the 30th ACM The Web Conference, 2021, in Ljubljana, Slovenia.
PY - 2021
Y1 - 2021
N2 - The problem of the increase in the volume of fake news and its widespread over social media has gained massive attention as most of the population seeks social media for daily news diet. Humans are equally responsible for the surge of fake news spread. Thus, it is imperative to understand people's behavior when they decide to share real and fake news items on social media. In an attempt to do so, we performed an analysis on data collected through a survey where participants (n= 363) were asked whether they were willing to share the given news item on their social media and explain the reasoning for their decision. The results show that the analysis presents several commonalities with previous studies. Moreover, we also addressed the problem of predicting whether a person will share a given news item or not. For this, we used intrinsic features from participants' open-ended responses and demographics attributes. We found that the perceived emotions triggered by the news item show a strong influence on the user's decision to share news items on social media.
AB - The problem of the increase in the volume of fake news and its widespread over social media has gained massive attention as most of the population seeks social media for daily news diet. Humans are equally responsible for the surge of fake news spread. Thus, it is imperative to understand people's behavior when they decide to share real and fake news items on social media. In an attempt to do so, we performed an analysis on data collected through a survey where participants (n= 363) were asked whether they were willing to share the given news item on their social media and explain the reasoning for their decision. The results show that the analysis presents several commonalities with previous studies. Moreover, we also addressed the problem of predicting whether a person will share a given news item or not. For this, we used intrinsic features from participants' open-ended responses and demographics attributes. We found that the perceived emotions triggered by the news item show a strong influence on the user's decision to share news items on social media.
KW - Emotion
KW - Fake news
KW - Misinformation
KW - News sharing
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85109003045&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85109003045
SN - 1613-0073
VL - 2890
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 2021 Workshop on Misinformation Integrity in Social Networks, MISINFO 2021
Y2 - 15 April 2021
ER -