Abstract
The abundant dissemination of misinformation regarding coronavirus disease 2019 (COVID-19) presents another unprecedented issue to the world, along with the health crisis. Online social network (OSN) platforms intensify this problem by allowing their users to easily distort and fabricate the information and disseminate it farther and rapidly. In this paper, we study the impact of misinformation associated with a religious inflection on the psychology and behavior of the OSN users. The article presents a detailed study to understand the reaction of social media users when exposed to unverified content related to the Islamic community during the COVID-19 lockdown period in India. The analysis was carried out on Twitter users where the data were collected using three scraping packages, Tweepy, Selenium, and Beautiful Soup, to cover more users affected by this misinformation. A labeled dataset is prepared where each tweet is assigned one of the four reaction polarities, namely, E (endorse), D (deny), Q (question), and N (neutral). Analysis of collected data was carried out in five phases where we investigate the engagement of E, D, Q, and N users, tone of the tweets, and the consequence upon repeated exposure of such information. The evidence demonstrates that the circulation of such content during the pandemic and lockdown phase had made people more vulnerable in perceiving the unreliable tweets as fact. It was also observed that people absorbed the negativity of the online content, which induced a feeling of hatred, anger, distress, and fear among them. People with similar mindset form online groups and express their negative attitude to other groups based on their opinions, indicating the strong signals of social unrest and public tensions in society. The paper also presents a deep learning-based stance detection model as one of the automated mechanisms for tracking the news on Twitter as being potentially false. Stance classifier aims to predict the attitude of a tweet towards a news headline and thereby assists in determining the veracity of news by monitoring the distribution of different reactions of the users towards it. The proposed model, employing deep learning (convolutional neural network(CNN)) and sentence embedding (bidirectional encoder representations from transformers(BERT)) techniques, outperforms the existing systems. The performance is evaluated on the benchmark SemEval stance dataset. Furthermore, a newly annotated dataset is prepared and released with this study to help the research of this domain.
Highlights
The year 2020 is marked by one of the major public health threats and emergency which the whole world witnessed due to outbreak of the coronavirus disease 2019 (COVID19) infection [1]
Social media like Twitter can ignite its consequences on the psychology of the society as these platforms are well known for rapidly communicating fabricated and distorted information, which usually carries the news based on the views and emotions of the users rather than the facts
This paper explores the reactions of Twitter users towards the Tablighi Jamaat (TJ) event that happened in mid-March 2020 in Delhi and became the most debatable topic if it is responsible for the outbreak of coronavirus infection in the country [15]
Summary
The year 2020 is marked by one of the major public health threats and emergency which the whole world witnessed due to outbreak of the coronavirus disease 2019 (COVID19) infection [1]. Social media like Twitter can ignite its consequences on the psychology of the society as these platforms are well known for rapidly communicating fabricated and distorted information, which usually carries the news based on the views and emotions of the users rather than the facts. On 31 March, the Union health ministry of India claimed that 30% of COVID positive cases in Delhi were found in linking with the Tablighi Jamaat incident. On 2 April, another news surfaced which said that this incident caused a doubling of coronavirus-infected cases. This news took a significant turn on social media, where users were increasingly calling its members responsible for the spreading of coronavirus across India. On 22 August, the Bombay High Court of India slams both media and electronic media for being part of political propaganda against Tablighi foreigners that aimed to manipulate the society into believing that they have spread the coronavirus in India and portray their picture as criminal [16]
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