credibility, anxiety, personal involvement, and social ties on rumor and truth .... This study serves as initiative attempt to investigate the differences between truth ...
Rumor and Truth Spreading Patterns on Social Network Sites during Social Crisis: Big Data Analytics Approach Mehrdad Koohikamali1, Dan J. Kim1, 1
College of Business, ITDS Department, University of North Texas, Denton, Texas {Mehrdad.Koohikamali, Dan.Kim}@unt.edu
Abstract. Social network sites give their users the ability to create contents and share it with others. During social crisis, the spread of false and true information could have profound impacts on users. Lack of prior studies to compare differences between diffusion patterns of rumors and truths during social crisis is the motivation of this study. In this study, we examine the role of information credibility, anxiety, personal involvement, and social ties on rumor and truth spread during social crisis. Building on the rumor theory, we propose a research model to examine differences between spread of rumors and truths. Using the Tweeter data collected during the Baltimore riots in 2015, we test the research model. Theoretical contributions and practical implications will be outlined based on the findings of the study. We anticipate findings will provide new avenues of research by determining characteristics of truths and rumors in online contexts. Keywords: rumor and truth in social crisis, spread patterns of rumor and truth, big data analytics, information diffusion.
1
Introduction
Social network sites (SNSs) provide a rich medium to generate content and share it with other users. People use SNSs for various reasons such as communicating, information seeking, maintaining close ties, building identity, information sharing, location disclosing, and educating [1, 2]. Understanding rumors diffusion pattern in online environments has been the focus of many studies in recent years [3]. However, isolating rumors from truths can be misleading without considering the spread of true information [4]. The way rumors spread is influenced by the absence of truths and truth presence could affect rumor diffusion. During social crisis and disasters, the uncertainty of information related to the event accompanied by the public anxiety and it increases negative consequences of rumors spread. Recent social crisis and events such as the Baltimore riots in 2015 indicate sharing information on social media has profound influence on involved subjects. In previous research, there is a gap to explore the differences between diffusion patterns of rumors and truth in social crisis and disaster situations on SNSs. This research gap,
specifically in the areas of rumor and truth diffusion on SNSs, leads this research to pose several research questions. In the SNS environment, we propose two questions: - What are the truth and rumor diffusion patterns during social crisis on SNSs? - How does the truth diffusion pattern is different from rumor?
2 2.1
Literature Review Information Diffusion on SNSs
People use SNSs for different purposes. According to prior research many people are aware of their intentions to use SNS. SNSs provide tools to create and share contents. SNSs have changed the way information is generated, distributed, and shared among many societies [5]. A micro-blogging service such as Twitter is mainly used for rapid information dissemination during social crises [5]. Rumors can spread in many contexts, but they are more prevalent in uncertain situations [3]. During the first stage of a social crisis many unproven facts should be rejected (rumors) or accepted (truths). During disasters people tend to fill in blanks, improvise news, and spread rumors [3]. 2.2
Rumor and Truth Spread on SNSs
Rumor has different meaning in different contexts. Unverified propositions for beliefs related to the topic of interest and uncertain truths about an involved subject are known as rumors [4]. Some researchers believe rumors are claims of facts about people, groups, events, and institutions without any proof of being true [6]. Rumor spreads in three phases: rumor parturition, rumor diffusion, and rumor controlling [3]. Rumor spread pattern occurs in two general forms. First, in social chain pattern a rumor moves from one person to another person with single interaction [7]. The second form of rumor spread pattern, known as multiple interaction network, and users receive a rumor from different users and send it to others [7]. 2.3
Information Credibility
Information quality is a multi-dimensional construct, and several models for the conceptualization and measurement of it exist. Research suggests that information quality is highly situational and depends on the source and content of information [8]. We adopt the information quality framework in the context of online reviews. In the context of online customer reviews, identifying true and false information is possible if readers have actual experience with products/services [8]. While during social crisis the rumor and truth are not easily separable due to the lack of enough evidences. In this study, for the content quality and reputation for source quality we adopt following dimensions: believability, relevancy, completeness, and concise representation [9].
3
Theoretical Background
Rumor theory explains the influence of ambiguous situations on spread of rumors [10]. During social crisis, many individuals’ beliefs are influenced by rumors because people tend to seek others’ opinions in such circumstances [11]. The theoretical foundation of this research is based on the rumor (mongering) model [5]. The rumor (mongering) model suggests rumors spread due to ambiguity of information, anxiety, personal involvement, and social ties [5]. Information credibility represents the quality of information. During crisis, the lack of information creates ambiguous and uncertain conditions [12]. Information credibility might reflect the content quality or the source quality. Content quality can be explained by believability, relevancy, completeness, and concise representation [9]. If the content of information is credible there is less doubt to correctly interpret the message [5]. Online information credibility is often judged based on the content [13]. In addition, credible sources are often believed to spread true information. During social crisis uncertain conditions provide both the source and content to influence the spread of rumors and truths. We propose, H1a: Information credibility positively influences the spread of true information. H1b: Information credibility positively influences the spread of rumors. Anxiety is a multidimensional construct and it can be explained as trait anxiety or state anxiety phenomena [14]. Uncertain conditions of social crisis cause higher anxiety among users [15]. Anxious people are more likely to seek information [16]. Moreover, in a SNS environment people are able to seek truthful information and subsequently lessen their anxiety. Likewise, we believe SNS users spread truths during uncertain conditions to soothe others as well as themselves. Therefore, we hypothesize: H2a: Anxiety positively influences truth spread. H2b: Anxiety positively influences rumor spread. The perceived importance of a social crises for a user plays an important role in rumor spread phenomena [3]. Expressions of personal involvement in rumors is positively related with rumor spread [3]. During social crisis on SNSs, people transmit more rumors if they feel they are involved [5]. Even though people want to refrain to pass rumors, they pass more rumors during crisis. Contrary to rumor spread, the truth spread is negatively influenced by personal involvement. We propose: H3a: Feelings of personal involvement negatively influences truth spread. H3b: Feelings of personal involvement positively influences rumor spread. Previous research show the relationship between existence of social ties and rumor spread [5]. Social ties are based on an existing social relation and the message is received from a known person has a greater chance of spreading [5]. Directed messages reflect strong ties if there is a two-way relationship and weak social ties do not influence the rumor spread. Similarly, the strength of social ties could be related with the spread of truth information due to the trustiness between ties. Thus, we hypothesize: H4a: Strong social ties positively influence truth spread on SNSs. H4b: Strong social ties positively influence rumor spread on SNSs. Following the rumor theory and proposed hypotheses, the posited research model is illustrated in Figure 1.
Information Credibility (2nd Order) H1 (+)
Anxiety
H2 (+)
Rumor/Truth Spread
H3 (+/-)
Personal Involvement H4 (+)
Strong Social Ties
Fig. 1. The proposed research model.
4
Methodology
To test and verify the proposed model a combination of coding procedure and machine learning algorithm of text mining will be used. The machine learning algorithm is based on the Koohikamali and Kim [17] study. We collected a Twitter dataset of Baltimore riots in 2015. During the period of the crisis from April 18, 2015 to May 03, 2015 we collected more than three hundred thousand tweets related to the Baltimore riots event. It includes a good example of social crisis that people used SNSs such as Twitter to generate and seek information ranging from calls to protest to pleas for prayer.
5
Expected Results and Contributions
This study will potentially contribute to both theory and practices in the area of social networking and information sharing. To best of our knowledge, this is the first study to examine the differences between the truth and rumor spread during rumor diffusion phase. We anticipate our study to contribute to the body of knowledge in many research areas by providing important aspects of rumor diffusion when truth is present. Results can be influential for research in communication, marketing, media, e-commerce, and information systems. The second contribution of this study is its emphasis on how information credibility influences the rumor and truth spread. We believe results of this study will broaden the current knowledge about online information dissemination.
6
Conclusion
This study serves as initiative attempt to investigate the differences between truth and rumor spreads on SNSs during social crisis. In this study we provided a research model to investigate the differences between rumor and truth spread patterns. It is built on the theory of rumor to explain effects of information credibility, anxiety, personal involvement, and strong social ties on rumor and truth spread.
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