Social Disclosure Behavior: Investigating Fake News Sharing on Social Media and News Verification Amidst the Covid-19 Pandemic

Ali Ab Ul Hassan*, Tayyeb Ramazan, and Rizwan Bashir Baloch

School of Creative Arts, The University of Lahore, Pakistan

*Corresponding Author [email protected]

Abstract

Spreading false information about health-related issues on social media platforms has drawn significant attention all over the world. Additionally, the reliance on social media for news consumption has made it probable for false news to be disseminated extensively as it is not expensive, easy to use, and quicker to send. During the COVID-19 pandemic, social media platforms have seen an increase in the sharing of information which has also contributed to the propagation of deceptive, false, and fake news. This study intends to analyze news verification behavior, social disclosure behavior, and fake news spreading during the COVID-19 pandemic. It was encouraged by serious concerns related to the widespread transmission of fake news and its influence on public health, trust, and social well-being. The data was gathered by an electronically administrated survey from social media users at different universities in Lahore with a sample size of 400. The study found that the general behavior of social media users is to not verify the news from other sources especially during crisis situations when the speed of news sharing increases extensively. This lack of verification contributes to the spread of fake news. The current study also found that disclosure behavior leads to the spread of fake news, while news verification behavior has a significant negative relationship with fake news sharing.

Keywords: disclosure behavior, fake news sharing, news verification behavior, social media

Introduction

COVID-19 created one of the most unprecedented global health crises in history however, it has also revolutionized the landscape of information dissemination, especially via social media platforms (Kapoor et al., 2020). Statistics show, that during the coronavirus pandemic, almost two hundred and fifty thousand people lost their lives. Moreover, four million were infected, either with light or severe physical problems (Tabish, 2020). Along with major health concerns, the spread of false information during Covid-19 was also a major issue. The director-general of the World Health Organization raised a concern and called it a parallel fight against the pandemic, as well as the infodemic (Naeem et al., 2021).

Due to advancements in technology, social media usage for spreading health-related information rapidly increased during the pandemic (Chen & Wang, 2021). Similarly, Pennycook et al. (2020) have also maintained that news and updates are primarily transmitted via social media platforms. The exceptional dependence on social media has given rise to a serious issue that is the widespread propagation of fake news related to COVID-19, posing substantial threats to public health, trust, and societal well-being (Zarocostas, 2020).

Any news article, story or piece of information based on false facts that can potentially mislead readers is considered “Fake News”, following the 2016 US presidential elections, this phrase has more meaning in today's digital media environment. (Allcott & Gentzkow, 2017).

The phenomena of fake news have been present, even before the invention of the World Wide Web (WWW). As a psychological warfare, news agencies and social media activists spread false information, in order to achieve maximum readership. Social media is a weapon in the warfare of the information age. It expands upon the examination of three discrete subjects which are news and information sharing, propaganda, and social networking (Prier, 2017). The ultimate goal is simple, to earn more revenue via clicks, catchy headlines and glittering headlines that persuade users to click impulsively (Aldwairi & Alwahedi, 2018). Internet users fall into the trap of fake news especially, the ones with minimum or no understanding of digital patterns and without verification or scrutiny, they start believing what they read or watch on social media platforms.

Using social media to consume news has its own drawbacks. People seek out and consume news from social media because it is easily accessible, less costly, easy to use, and can transmit information quickly. Due to this, the fake news or the low-quality news that contains purposefully misleading information begin to proliferate widely (Shu et al., 2017). The social media has the immense power to spread information quickly as with the usage of specific algorithms and hashtags, the technological experts can accelerate the reach of a social media post and make it viral.

Fake news sharing on social media is now a global concern. It sets the patterns of the news coverage and transmission. During the COVID-19 outbreak, fake news sharing was a serious concern due to the rapid sharing of information related to the virus and pandemic. In the process of news sharing both authentic and unauthentic news are disseminated without the filters of news verification (Talwar et al., 2020).

Sharing of the fake information is considered as now an information disorder (Castioni et al., 2022). Thus, fake news is inherently more likely to be shared than other types of news. (t'Serstevens et al., 2022).

Fake news is changing societal values and opinion on the serious issues of the society. It is affecting the dynamics of information sharing. Due to the change in information sharing, the fake news (FN) is replacing the truth news (TN) in different societies (Olan et al., 2022).

This study aims to investigate the relationship between social disclosure behavior and fake news sharing among university students during COVID-19. In addition, it explores the connection between news verification behavior and fake news sharing. As per Derlega and Grzelak (1979) Disclosure is a goal-directed behavior, with people engaging in it to achieve a variety of objectives, including improving intimacy in significant personal relationships and expressing themselves. Self-disclosure goals act as a mediator between media affordances and disclosure intimacy, and people pursue strategic goals and disclose differently based on social media affordances (Bazarova & Choi, 2014).

The general behavior of users is to not verify the news of social media from other sources in terms of routine news. Whereas, during the time of crisis, the speed of news sharing either its true or untrue speeds up because people are eager to share the information quickly (Plotnick, 2019).

This study is crucial to understand the fundamental psychology of social media users as the dynamics of social and digital sphere are drastically opposite. In the public gatherings, thoughts of people are constraint by social factors while in digital sphere, online users are not afraid of the prevailing social stigma in the society. During the COVID-19 pandemic in Pakistan, lockdown was implemented and social and commercial activities were seized. Along with business, academic activities were also hindered and schools and universities were shifted to online module. As students were forced to stay at home 24/7, the virtual learning encouraged them to attend online classes. The usage of social media increased during lockdown and due to the lack of public and physical gatherings, people started expressing themselves on digital platforms especially on social media. The COVID-19 related news such as, death toll, vaccination process and patient’s personal experiences were on trending. People were sharing COVID-19 related news including rumors without verifying. As a result of this, self-disclosure behavior accelerated resulting in the wide spread of fake news during the pandemic. People shared fake news online during the COVID-19 pandemic, a period of unprecedented growth for the dissemination of false information (Balakrishnan et al., 2021). This study contributes in the spectacle of global issue, related with fake news disseminating on social media.

Literature Review

Social media users are reluctant to use other verification tools to authenticate the social media information. The awareness of fake news campaigns and the usage of news verification behavior can eliminate the sharing of fake news on social media. This awareness can create a sense of verification before the information is shared. News verification behavior also increases self-efficacy and reputation concerns among individuals. (Apuke et al., 2023)

Social media developers and reporting companies can mutually combat the fake news sharing phenomenon which is increasing with every new day. There are multiple factors which contribute to the verification of information available online. The prominent factor is the awareness of the utilization of information and social media usage literacy. (Majerczak & Strzelecki, 2022). Two distinct behaviors associated with disseminating fake news can be anticipated among those who utilize social media to pursue social comparison. First and foremost is to earn social acceptability where entities may try to authenticate convinced news or data that they believe is relevant to their social networking community. Second, in order to maintain a positive picture in the eyes of others and to represent themselves as having more accurate information than others, people share news without validation. However, the employers should refrain from sharing any news that appears to be false (Domenico et al., 2021).

Several factors affecting the exchange of COVID-19 data are investigated. Islam et al. (2020) discovered that self-promotion and entertainment could encourage the spreading of false material about COVID-19 on social media. Users trust in online material and the perception of information overwork were significant analysts of unsupported material sharing. As a result, the dissemination of confirmed information about COVID-19 has not been thoroughly examined and in fact required more investigation.

In the field of information warfare, the government's main focus areas have been combating extremist social media, encountering fake news, and intercepting election tampering. Covid-19 spawns a refutation and challenges the authority and legitimacy of the government in control. Cyberattacks are crucial and generate threats to public health as these attacks have long-lasting impacts on the general public. The validity of the government is called into question if it is unable to defend and preserve its people. Legitimacy is more about who can govern than who can lead. To fail to protect is to be unable to lead the country (Kallberg et al., 2020)

Prior to examining social media as a tool of modern warfare with the analysis of propaganda, social networking and exchange of information, the study also demonstrates how digital information processing is becoming the latest arsenal of combat. By inserting itself into an already existing narrative and then amplifying it through a network of automated "bot" accounts, the propaganda message is disseminated and eventually causes the social media platform's algorithm to identify it as a trending subject (Prier, 2017).

The spread of fake news is gradually acknowledged as a security issue spanning several academic fields therefore, a cross-disciplinary strategy will be necessary to address the issue. The fake news and the dissemination of deceptive information can be assumed as a sign of futuristic hybrid warfare. The emotional element is crucial for the effectiveness of deceitful information because without the emotional value, the information can be overlooked. The computational linguistics needs to pinpoint differences between true news and FN in order to objectively characterize the content of genuine news. Furthermore, the genuine pattern spread of news is different from fake news because it uses bots and trolls to flood the news horizon (Sample et al., 2019).

Online news gave rise to a new set of worries in the 2000s. One of which was that too much diversity of opinion would facilitate the formation of "echo chambers" or "filter bubbles" by like-minded people, isolating them from opposing opinions (Sunstein, 2001). Facebook uses different pattern than other social media platforms that is why, the information can be spread between users without filtering and editorial review. Additionally, in some cases an individual with no such track record can attain as much viewership as CNN or the New York Times (Allcott & Gentzkow, 2017).

The detection of fake news on social media is challenging as compared to the traditional media whose controlling algorithm and findings are a technical task. Fake news is deliberately generated with the intent of misleading readers. Besides, it creates a true-like impression which makes it hard to detect. In order to troubleshoot fake news, supporting information should be included such as engagements on social media (Shu et al., 2017).

Theoretical Framework

Many theories related to the information sharing and its verification deal with the phenomenon of false information and fake news. Information literacy is one of the key elements in this regard to counter fake news sharing and provides a detailed theoretical framework. There are many reasons for sharing fake news. One of them is a conspiracy. Conspiracy theory deals with the reasons and process of conspiracy construction. In the case of social media news sharing, much information is shared without verification due to the race of information sharing. During COVID-19, the flow of information was at its peak on social media. The theory of informative fictions (TIF) is one of the contemporary theories that deals with the construction and sharing of news (2020). The theory differentiates between the two elements that deal with it. They are known as the objects and the agents. The theory also proposed the competition between property information and character information. Character information can be constructed on the false claims which were processed through the sharing of information. Misinformation is a complex issue which cannot be traced through a single framework. Another reason is the social competition in information sharing. The study also got help from the social comparison theory (1954) to know the social race between the individuals about information sharing. With the help of these theoretical frameworks, the research develops its hypothesis and collects the data in light of these hypotheses.

H1: Social disclosure behavior leads to fake news sharing regarding COVID-19.

H2: News verification behavior reduces the trend of fake news sharing regarding COVID-19.

Figure 1

Hypothetical Model

Methodology

In this study, survey method was used to collect the data from respondents. Dillman et al. (2014) stated that the usage of surveys allows for the collection of data from a wide range of respondents in a very short period of time thus, make it a very useful data collection technique. It consisted of standardized questions that decreased the potential bias while filling the questionnaire. To ensure the accuracy and validity of the results, it was essential to address common method bias (CMB) when the data was collected by survey technique. CMB occurs when both independent and dependent and unobserved variables data are collected in the same survey (Podsakoff et al., 2003). To avoid CMB, first of all the anonymity of the respondents should be ensured. It is significant as when the respondents feel that their responses are confidential, they are more likely to provide honest and unbiased feedback. Some of the question items were also incorporated reversely, which were coded again using SPSS. After data collection, Harmon et al. (1997) test of one factor was run in SPSS, the Harmon single factor test was sensitive enough to determine if common method bias was strong enough to influence the results (Fuller et al., 2016). The value 41.2% of the explained variance was less than 50%. However, a common rule of thumb is that if a single factor accounts for more than 50% of the total variance, it raises concerns about common method bias (Cheung et al., 2008).

The current research was based on a quantitative study that adhered to information collection through questionnaires and used a cross-sectional study and the electronic survey was administered because of the 2020 epidemic. The study was conducted during the first wave of COVID-19 (March-April 2020). The population of this study was social media users from different universities in Lahore. For this purpose, four top universities from general category list of HEC were taken including two from government sector and two from private sector. Non-probability and convenience sampling techniques were used to get the data. Creswell and Creswell (2017) justified convenience sampling as when time and resources are on the lesser side convenience sampling is a practical option. Researches in the social sciences were normally conducted upon the non-probability sampling techniques despite the fact that probability sampling techniques are believed to be ideal (Rowley, 2014). There is no scientific significant relationship between the quality of research and sampling strategy. Despite its generalizability, probability sampling is not always appropriate or necessary for many circumstances (Mumtaz et al., 2017). Moreover, for applying probability sampling technique, the sample frame is an essential part as without the list of all units, probability sampling cannot be applied (Saunders et al., 2017). So, in this study non probability convenience sampling was used.

The thumb rule of the number of items multiplied by 10 was applied to get the sample size (Heir et al., 2013). Hence in this study, a sample size of 400 participants was taken which is well ahead according to the thumb rule. In this study, there were three constructs and demographic variables and all the items were measured by close-ended questions. The constructs were measured on an already reliable and valid built-in scale. The three-item scale (Talwar et al., 2020) was used to determine news verification behavior on five-point Likert scales that ranged from 1= Strongly Disagree to 5= Strongly Agree. The five-item scale developed by (Apuke & Omar, 2021) was used to determine online fake news sharing on a Five-Likert scale alternating from 1= intensely disagree to 5= come to an understanding. Social disclosure behavior was measured by using the scale of Ranzini et al. (2020).

Data Analysis

The data was collected from four hundred participants in which 35.3 % were males and 65% were female respondents. There were four age categories of the respondents in which 59% of the participants were 20-30 years old and almost 38% were of the age 31-40. At the education level, majority of the students were graduates consisting of 51% of the participants. Similarly, 45% of the respondents were masters. In marital status, 72% of the respondents were single and almost 28% were married.

Table 1

Demographics

Table 2

Descriptive Statistics

The current study in which social disclosure behavior included 5 items having a mean value of 3.68 with a standard deviation of 0.98 and a 0.87 Cronbach Alpha value which is well above the standard value of 0.7. Fake news sharing consists of 4 items which have a mean value of 3.54 with a standard deviation of 1.02 and a Cronbach alpha value of 0.86. Similarly, news verification behavior includes 4 items, having a mean value of 2.40 and a standard deviation of 0.99 and Cronbach's alpha is 0.88.

Table 3

Pearson Correlation

Note. **p< .01.

The Pearson correlation matrix shows that there is a strong relationship between fake news sharing and social disclosure behavior (r = 0.30, p < 0.000) while there is a highly significant negative relationship between social disclosure behavior and news verification behavior as SDB increases the NVB decreases (r = -0.634, p < 0.000). Similarly, news verification behavior and fake news sharing also have a significant negative relationship (r = -0.3, p < 0.000).

It was found that there was no significant difference among the education level, experience level, gender and marital status. So, the regression analysis has been run without segmentation demographically. Moreover, multicollinearity issue is usually checked when multiple regression is run but in this case, simple regression is run keeping one independent variable and one dependent variable. However, when the multicollinearity was checked, there was no issue of found as VIF value was 1.7 which was well below from 5.

H1: Social disclosure behavior leads to fake news sharing regarding COVID-19.

In Hypothesis I, the table shows that social disclosure behavior leads to fake news sharing and in the one-unit change of social disclosure behavior fake news sharing increases by 0.312 units significantly. Although the value of R square, the coefficient of determination is on the lower side still the dependence of fake news sharing on social disclosure behavior is significant as b = 0.312, t = 6.27, p < 0.000.

H2: News verification behavior reduces the trend of fake news sharing regarding COVID-19.

In Hypothesis II, the table shows that news verification behavior reduces the tendency of fake news sharing and in the one-unit change of news verification behavior, fake news sharing decreases to 0.30 units significantly. Although the value of R square, the coefficient of determination is on the lower side still the dependence on reducing the sharing of fake news on news verification behavior is significant. As (b = -0.30, t = 6.50, p < 0.000).

Table 4

Regression Analysis

Figure 2

Statistical Model

Discussion

Social media provides a very convenient platform to its users to spread the news. Hence, the analysis of social media disclosure behavior revealed that individuals who have the tendency to disclose behavior are more likely to spread fake news regarding COVID-19. The research work of Sampat and Raj (2022) also revealed that sharing news as a disclosure behavior is significant and plays a primary role in sharing fake news. On the other hand, those who are more enthusiastic about the verification of news do not like to share fake news. Majerczak and Strzelecki (2022) endorsed that fake news sharing is reduced due to the news verification behavior and involvement of the larger community. Media literacy is important to understand the dynamics of digital media. Furthermore, in order to combat fake news phenomenon, the consumers of digital content must be aware of the psychology of the social media users. News verification behavior increases the tendencies of cross checking the fake news in youth. Additionally, the rise in news verification behavior reduces the spread of fake news.

Limitations

This study has also certain limitations. So, future studies can be conducted by adding more variables to the study to understand the antecedents. It is also recommended that this study should be replicated by focusing on different social media platforms individually, rather than being applied to the entire social media, wholistically. Moreover, the respondents of this study were students only. So, further studies should be carried out by including all the citizens belonging to different age groups, professions and gender.

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