Information sharing on social media sites

This study reports on an exploratory survey conducted to investigate the use of social media technologies for sharing information. This paper explores the issue of credibility of the information shared in the context of computer-mediated communication. Four categories of information were explored: sensitive, sensational, political and casual information, across five popular social media technologies: social networking sites, micro-blogging sites, wikis, online forums, and online blogs. One hundred and fourteen active users of social media technologies participated in the study. The exploratory analysis conducted in this study revealed that information producers use different cues to indicate credibility of the information they share on different social media sites. Organizations can leverage findings from this study to improve targeted engagement with their customers. The operationalization of how information credibility is codified by information producers contributes to knowledge in social media research.     

What kind of #conversation is Twitter? Mining #psycholinguistic cues for emergency coordination

The information overload created by social media messages in emergency situations challenges response organizations to find targeted content and users. We aim to select useful messages by detecting the presence of conversation as an indicator of coordinated citizen action. Using simple linguistic indicators drawn from conversation analysis in social science, we model the presence of coordination in the communication landscape of Twitter¹ using a corpus of 1.5 million tweets for various disaster and non-disaster events spanning different periods, lengths of time, and varied social significance. Within replies, retweets and tweets that mention other Twitter users, we found that domain-independent, linguistic cues distinguish likely conversation from non-conversation in this online form of mediated communication. We demonstrate that these likely conversation subsets potentially contain more information than non-conversation subsets, whether or not the tweets are replies, retweets, or mention other Twitter users, as long as they reflect conversational properties. From a practical perspective, we have developed a model for trimming the candidate tweet corpus to identify a much smaller subset of data for submission to deeper, domain-dependent semantic analyses for the identification of actionable information nuggets for coordinated emergency response.     

Understanding motivated publics during disasters: Examining message functions,frames, and styles of social media influentials and followers

There has been a growing body of research regarding how organizations and general publics communicate on social media during crises. Integrating the uses and gratifications perspective, the social‐mediated crisis communication model, and the framing approach, our study offers a consolidated framework explaining how and why motivated social media publics communicate during crises. Namely, we examined whether and how influentials and followers employed different message functions through communicative devices including frames and styles. A content analysis was conducted on 800 tweets sampled from influentials and followers discussing the 2017 Ariana Grande concert bombing disaster. Our results (N = 800) suggested that influentials and followers adopted distinct communicative functions on social media during the disaster. Influentials engaged in information sharing and support exchange, whereas followers engaged in opinion expression and emotional coping. Influentials and followers also adopted specific frames and styles to achieve these communicative functions. Our findings can help crisis communicators understand the needs, concerns, and communication features of different publics and construct effective messages to reach them.     

Spatial biases in crowdsourced data: Social media content attention concentrates on populous areas in disasters

The objective of this study is to examine and quantify the relationships among sociodemographic factors, damage claims, and social media attention on areas during natural disasters. Social media has become an important communication channel for people to share and seek situational information to learn of risks, to cope with community disruptions, and to support disaster response. Recent studies in disaster informatics have recognized the presence of bias in the representation of social media activity in areas affected by disasters. To explore related factors for such bias, existing studies have used geo-tagged tweets to assess the extent of social media activity in disaster-affected areas to evaluate whether vulnerable populations remain silent on social media. However, less than 1% of all tweets are actually geo-tagged; therefore, attempts to understand the representativeness of geotagged tweets to the general population have shown that certain populations are over- or underrepresented. To address this limitation, this study examined the attention given to locations based on social media content. The study conducted a content-based analysis to filter tweets related to 84 super-neighborhoods in Houston during Hurricane Harvey and 57 cities in North Carolina during Hurricane Florence. By examining the relationships among sociodemographic factors, the number of damage claims, and the volume of tweets, the results showed that social media attention concentrates in populous areas, independent of education, language, unemployment, and median income. The relationship between population and social media attention is characterized by a sub-linear power law, indicating a large variation among the sparsely populated areas. Using a machine-learning model to label the topics of the tweets, the results showed that social media users pay more attention to rescue- and donation-related information; nevertheless, the topic variation is consistent across areas with different levels of attention. These findings contribute to a better understanding of the spatial concentration of social media attention regarding posting and spreading situational information in disasters. The findings could inform emergency managers and public officials to effectively use social media data for equitable resource allocation and action prioritization.     

Microblog summarization using self-adaptive multi-objective binary differential evolution

Social media platforms become paramount for gathering relevant information during the occurrence of any natural disaster. Twitter has emerged as a platform which is heavily used for the purpose of communication during disaster events. Therefore, it becomes necessary to design a technique which can summarize the relevant tweets and thus, can help in the decision-making process of disaster management authority. In this paper, the problem of summarizing the relevant tweets is posed as an optimization problem where a subset of tweets is selected using the search capability of multi-objective binary differential evolution (MOBDE) by optimizing different perspectives of the summary. MOBDE deals with a set of solutions in its population, and each solution encodes a subset of tweets. Three versions of the proposed approach, namely, MOOTS1, MOOTS2, and MOOTS3, are developed in this paper. They differ in the way of working and the adaptive selection of parameters. Recently developed self-organizing map based genetic operator is explored in the optimization process. Two measures capturing the similarity/dissimilarity between tweets, word mover distance and BM25 are explored in the optimization process. The proposed approaches are evaluated on four datasets related to disaster events containing only relevant tweets. It has been observed that all versions of the developed MOBDE framework outperform the state-of-the-art (SOA) techniques. In terms of improvements, our best-proposed approach (MOOST3) improves by 8.5% and 3.1% in terms of ROUGE??2 and ROUGE?L, respectively, over the existing techniques and these improvements are further validated using statistical significance t-test.

     

Police message diffusion on Twitter: analysing the reach of social media communications

Social media are becoming increasingly important for communication between government organisations and citizens. Although research on this issue is expanding, the structure of these new communication patterns is still poorly understood. This study contributes to our understanding of these new communication patterns by developing an explanatory model of message diffusion on social media. Messages from 964 Dutch police force Twitter accounts are analysed using trace data drawn from the Twitter^? API to explain why certain police tweets are forwarded and others are not. Based on an iterative human calibration procedure, message topics were automatically coded based on customised lexicons. A principal component analysis of message characteristics generated four distinct patterns of use in (in)personal communication and new/versus reproduced content. Message characteristics were combined with user characteristics in a multilevel logistic general linear model. Our main results show that URLs or use of informal communication increases chances of message forwarding. In addition, contextual factors such as user characteristics impact diffusion probability. Recommendations are discussed for further research into authorship styles and their implications for social media message diffusion. For the police and other government practitioners, a list of recommendation about how to reach a larger number of citizens through social media communications is presented.     

Social media and credibility indicators: The effect of influence cues

Guided by the MAIN model, this study examines how individuals evaluate the source credibility of tweets and retweets based on non-content attributes. Three types of heuristics were examined, including authority, identity, and bandwagon cues. Findings suggest that all three heuristics impacted source credibility perceptions to some extent. Authority cues most strongly influenced source credibility perceptions, and cue-cumulative effects were demonstrated in which different heuristics triggered by different agency cues increased perceptions of credibility. Moreover, the presence of retweets reduced perceptions of source credibility compared to conditions with no retweets.     

Expanding the Impression Management Model of Communication Channels: An Information Control Scale

According to O’Sullivan's (2000) impression management model of communication channels, individuals will prefer to use mediated channels rather than face‐to‐face conversation in face‐threatening situations. Within his model, this trend is due to the channel features that allow for control over exchanged social information. The present paper extends O’Sullivan's model by explicating information control as a media affordance, arising from channel features and social skills, that enables an individual to regulate and restrict the flow of social information in an interaction, and present a scale to measure it. One dimension of the information control scale, expressive information control, positively predicted channel preference for recalled face‐threatening situations. This effect remained after controlling for social anxiousness and power relations in relationships.     

Disaster Warnings in Your Pocket: How Audiences Interpret Mobile Alerts for an Unfamiliar Hazard

This study investigates how people interpret Wireless Emergency Alerts (WEAs) and Twitter‐length messages (‘tweets’) delivered over mobile devices for an unfamiliar hazard. Specifically, through four (N = 31) focus groups and 31 think‐out‐loud interviews, participants’ understanding of, belief in and personalisation of WEAs and tweets were assessed for a mock improvised nuclear device detonation in a major U.S. metropolitan area. While participants offered a wide variety of interpretations, WEAs and tweets were often deemed confusing, difficult to believe and impersonal. Participants also consistently found WEAs and tweets to be fear inducing and uninformative. The findings compel improvements in the way that WEAs and tweets are currently written, as well as indicate future directions for applied risk and crisis communication theory development.     

Ranking versus reputation: perception and effects of search result credibility

Search engines play a key role for Internet users when searching for information. The vast majority of users are heavily influenced by the given ranking on the search engine results page (SERP). In this study, N?=?222 university students were tasked to inform themselves about the working conditions in South Asia on the basis of given SERPs. Besides the ranking on the SERP, two credibility cues – the type of the website (news site, corporate website, research institute, and private blog) and the primary source of information mentioned in the search result (scientific study vs. corporate spokesperson) – were varied. Two research objectives were examined: the influence of the ranking and the credibility cues on the evaluation of search results; and the effect of both ranking and credibility cues on the selection. Credibility cues had a strong influence on the perception of the search results’ credibility. Students rated the credibility higher if search results linked to reputable websites or mentioned a neutral primary source of information. We also find an interaction effect between the type of website and the primary source of information. However, participants’ selection was mainly influenced by the ranking. Reasons for this discrepancy are discussed.     

How much Klout do you have … A test of system generated cues on source credibility

Social media provides a great deal of information about the users; whether it is personal likes or dislikes, social connections and networks, or general emotional states in ways not previously available to others. As a result, judgments and perceptions of a person’s credibility can be made from examining posts, tweets, or other indicators on social media (Westerman, Spence, & Van Der Heide, 2012). Because social media users create their own content, the question of how others make judgments about credibility is important (Haas & Wearden, 2003). However, until recently, a single indicator of a person’s influence on social media networks did not exist. Klout.com developed an popular indicator of this influence that creates a single score based on the idea that “everyone has influence—the ability to drive action”. The purpose of the study is to determine whether and to what degree a Klout score can influence perceptions of credibility. Results demonstrated that the mock Twitter page with a high Klout score was perceived as higher in dimensions of credibility than the identical mock Twitter page with a moderate or low Klout score.     

A social network as information: The effect of system generated reports of connectedness on credibility on Twitter

Social media have gained increased usage rapidly for a variety of reasons. News and information is one such reason. The current study examines how system-generated cues available in social media impact perceptions of a source’s credibility. Participants were asked to view one of six mock Twitter.com pages that varied both the number of followers and the ratio between followers and follows on the page and report their perceived source credibility. Data indicate that curvilinear effects for number of followers exist, such that having too many or too few connections results in lower judgments of expertise and trustworthiness. Having a narrow gap between the number of followers and follows also led to increased judgments of competence. Implications of these findings are discussed, along with limitations of the current study and directions for future research.     

Unfriend or ignore tweets?: A time series analysis on Japanese Twitter users suffering from information overload

In recent years, with increased opportunities to post content on social media, a number of users are experiencing information overload in relation to social media use. This study addresses how Japanese Twitter users suffering from information overload cope with their stress, focusing on two actions: (1) The “unfriending” activities and (2) The changes in tweet processing methods. Objective data, such as numbers of friends, were collected through Twitter's open Application Programming Interfaces (APIs), and subjective data, such as perceived information overload and tweet processing methods, were collected through a web-based survey as a panel dataset (n = 778). The results demonstrated that although users experience information overload, they continue to increase their number of friends, and that the users who experience information overload modify their usage habits to avoid seeing all received tweets. In short, users do not choose a strategy to reduce the absolute number of received tweets, but only a strategy that involves changing the processing method of the received tweets.     

Is communication competence still good for interpersonal media?: Mobile phone and instant messenger

The concept of communication competence has developed in the area of nonmediated interpersonal communication. With the advent of digital media, interpersonal communication has been heavily dependent on interpersonal media. The sharp distinction between theories for nonmediated communication and mediated communication is disappearing. The interconnectedness of face-to-face communication and mediated interpersonal communication is a salient current phenomenon. To explore the relation between two communication types this study investigated the relevance of the concept of communication competence with the interpersonal digital media; mobile phone, SMS, and instant messenger. Three facets were examined in particular: namely, the direct effects of communication competence and the indirect effects through individuals’ cognitive process for interpersonal media and individuals’ characteristics in interpersonal communication. The hypothesized model of mediated interpersonal communication competence was analyzed using structural equation model. The results revealed that communication competence was positively associated with mediated interpersonal communication competence. The indirect effects of communication competence through media efficacy and social presence were empirically supported. Relationship maintenance was found to mediate the effect of communication competence on mediated interpersonal communication competence. The links of two different communication fields and the theoretical implications of the findings were further discussed.     

Information Needs and Communication Gaps between Citizens and Local Governments Online during Natural Disasters

A growing number of citizens and local governments are using tweets to communicate during natural disasters. A good understanding of the communication contents and behaviors is critical for disaster relief. Previous work has used crisis taxonomies or manually labeling methods to understand the content. However, such methods usually require extra efforts to find insights related to specific events. In this paper, we use a semi-automatic framework to extract specific topics from the communication contents of citizens and local governments, combined with the spatiotemporal information to explore: 1) the spatiotemporal bursts of topics; 2) the change of topics with respect to the severity of disaster; and 3) communication behaviors. We use tweets collected during 18 snowstorms in the State of Maryland, US, as a case to study. The study reveals the communication differences due to the urban-rural divide or to the severity of the snowstorms. The insights suggest that local governments could potentially adapt the context of information delivered to citizens so as to match their needs.     

Exploring the impact of ethnic identity through other-generated cues on perceptions of spokesperson credibility

Although previous studies indicate that perceived similarity can influence perceptions of source credibility, less is known about the impact of ethnic identity on these perceptions in social media environments. A quasi-experiment was designed to manipulate the strength of ethnic identity of an African American spokesperson promoting a health news story. The results indicate a substantive condition by participant ethnicity interaction, in which African Americans assign greater credibility to high ethnic identity spokespeople, while Caucasian respondents found low ethnic identity spokespersons more credible. The results are discussed in terms of the understanding of credibility perceptions across diverse audiences, and the implications for health communication professionals working with historically underrepresented populations.     

A conceptual framework for developing solutions that organise social media information for emergency response teams

ABSTRACT

Social media have great power to spread information, and this is particularly noticeable when an emergency occurs. The extraction of accurate information from social media can offer an important resource for emergency management, both in terms of decision-making and increasing situational awareness. This paper describes a conceptual framework for the development of applications to treat messages from social media. It is designed to select, classify and prioritise, using parameters, messages containing information that is relevant to the emergency context. It allows a team to act on this information and to generate rescue actions that contribute to the emergency solution. It has a collaborative bias, providing perceptual, coordination and communication mechanisms. We also present an instantiation and the simulation of its use in the treatment of tweets (Twitter messages) about two emergencies: an earthquake in Mexico City (19/09/2017) and a California fire (December, 2017). The volume of messages is enormous, but most of them do not present significant value to the emergency response. We categorised those that contained relevant information. With only 2% of the tweets, it was possible to identify and prioritise messages with potential to aid in response and rescue operations.     

Should I trust him? The effects of reviewer profile characteristics on eWOM credibility

For online consumer reviews to serve as decision-making aids, users have to first trust the reviewer. However, unlike face-to-face communication, where trust develops overtime, consumers have to rely on personal profile information to establish confidence in the reviewer in online shopping context. These personal profile characteristics may serve as cues of source credibility. This study adopts a 2 (number of trusted members: small, large) × 2 (profile picture: without, with) × 2 (review valence: negative, positive) between-participants experiment to explore how two personal profile characteristics, reputation cue and profile picture, influence cognitive trust and affective trust towards the reviewer and perceived review credibility respectively and in a combinatory manner. The findings of the study showed that reputation cue and profile picture cue contributed differently to users’ affective trust and cognitive trust towards the reviewer. Reputation cue, generated by the system, was found to influence both affective and cognitive dimensions of trust, whereas the self-generated cue of profile picture affected only affective trust. Reputation cue had a direct influence on perceived review credibility, whereas the influence of profile picture on perceived review credibility was dependent upon review valence. The implications of these findings are discussed in the paper.     

The Hyperlinked World: A Look at How the Interactions of News Frames and Hyperlinks Influence News Credibility and Willingness to Seek Information

Prior research has identified the influence of using hyperlinks in online information gathering. This study attempts to understand first, how hyperlinks can influence individuals' perceptions of news credibility and information‐seeking behavior. Second, the paper extends previous research by examining the interaction of hyperlinks with the content of the story. In doing so, the paper examines the influence of hyperlinks on news frames. The data for the study were collected using 2 experiments embedded in web‐based survey of participants. Findings show that hyperlinks in news stories can increase perceptions of credibility as well as information‐seeking. Results reveal the interaction of news frames in the process; hyperlinks increase participants' perception of news credibility; but only in the value‐framed condition. Implications are discussed.     

一种相关话题微博信息的筛选规则学习算法

微博作为一种新型的社会媒体,以其信息的高实时性、话题动态关注、传播速度快的特点,逐渐被人们所接受和使用。筛选出相关话题的微博信息,帮助用户关注话题的动态发展,成为迫切需要解决的问题。由于微博信息篇幅极短、包含的信息和特征少等特点,为相关话题微博信息的筛选带来了新的挑战,而传统的文本分类技术已不再适用。该文提出了基于信息熵的筛选规则学习算法,利用学习得到的规则对微博信息进行有效的筛选。算法利用信息熵来评价规则的好坏,同时基于模拟退火的随机策略使算法中的规则选择避免了过于贪心。分别通过来自新浪微博的约九万条标注数据和TREC2011中约三千条特定话题的标注数据进行实验,该文算法相比于CPAR和SVM算法,学习得到的规则在筛选时取得了较高的F值。