Content Analysis of a Live CDC Twitter Chat During the 2014 Ebola Outbreak

A public response to a looming health threat may be marked with misinformation and panic. However, providing the public with accurate information and updates may be an effective way to prevent widespread fear. In response to the 2014 Ebola panic in the United States, the U.S. Centers for Disease Control and Prevention (CDC) initiated a Twitter conversation with the public to alleviate concerns and provide accurate information about the disease. This study conducted a content analysis of 512 randomly selected tweets by the general public directed to the CDC. The major themes identified included the etiology of Ebola, policy, the environment, spread and scope of the disease, fear and anxiety from the public, and misinformation. Practical implications of these findings include encouraging government and emergency health response organizations to prepare educational messages and materials in advance that detail responses to common questions, such as transmission and symptoms.     

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The media are normatively expected to play significant roles in conflictual discussions within national and international communities. As previous research shows, digital platforms make scholars rethink these roles based on media behavior in online communicative environments as well as on the structural limitations of the platforms. At the same time, traditional dichotomies between information dissemination and opinion formation roles, although seemingly universal, also vary across cultures. We look at four recent conflicts of comparable nature in the United States, Germany, France, and Russia to assess the roles that legacy media have performed in the respective ad hoc discussions on Twitter. Our approach differs from previous studies, as we combine content analysis of tweets by the media and journalists with the resulting positions of the media in the discussion graphs. Our findings show that, despite the overall trend of the “elite” and regional media sticking to information dissemination, online-only media and individual journalists vary greatly in their normative strategies, and this is true across countries. We also show that combining performance in content and social network analysis may allow for reconceptualization of media roles in a more flexible way.     

Is there Lingua Franca in informal scientific communication? Evidence from language distribution of scientific tweets

Language distribution in scientific communication reflects the influence of different languages on science in global perspective. The study, based on over 450 thousand scientific tweets of all publications indexed by Scopus in June 2015, reveals the language distribution in informal scientific communication. Moreover, this result is compared with the language distribution in formal scientific communication reflected in scientific publications. Results show: (1) The language of scientific tweets is concentrated in English (91%), Japanese (2.4%) and Spanish (1.7%), while the language of scientific publications is concentrated in English (90.6%), Chinese (5%) and German (1.1%). (2) Both scientific tweets and scientific publications present disciplinary differences in language distribution, reflecting the different amount of attention that authors of different languages have on certain disciplines. (3) Except Saudi Arabia, investigated countries all over the world, regardless of whether their native language is English or not, all have English scientific tweets in the dominant position. For the vast majority of these countries, the native language scientific tweets only rank the second position. (4) Overall, 26% of tweeters use more than one language to tweet scientific products, while 49% of scientific tweeters tweet everything in English only. The results indicate that English has undoubtedly become the lingua franca in informal scientific communication.     

Envy on social media: The good,the bad and the ugly

Observing the positive aspects of others’ lives on social media (SM) can bring about envy among users. Drawing from social comparison and technology acceptance theories, this study develops a research model to explain how envy occurs and impacts SM users’ behavior. In this work, we conducted two studies across three different SM settings to investigate two types of envy, benign and malicious envy. The results show that malicious envy is negatively related to the dependent variable of SM use intention while benign envy facilitates it. The findings provide many valuable contributions to both information systems (IS) academia and industry. This study identifies the unique SM factors intertwining with envy. Moreover, this work helps SM users and practitioners be aware of the potential envy issue on SM so they can take effective actions to enhance SM use.     

微博视野下大学生思想政治教育对策探讨

作为一种新兴的网络媒体传播方式,微博满足了当代大学生关注社会、交流思想的需求,逐渐成为当代大学生获取信息、进行交流的重要工具。微博一出现就对大学生的思想行为产生很大影响,高校理应充分重视并运用这一新媒介对大学生进行思想政治教育,要增强运用微博开展大学生思想政治教育的自觉意识,积极构建大学生思想政治教育的微博群,发挥微博平台的舆论监测和思想引导作用,培养大学生的媒介理性。     

Investigating the COVID-19 vaccine discussions on Twitter through a multilayer network-based approach

Modeling discussions on social networks is a challenging task, especially if we consider sensitive topics, such as politics or healthcare. However, the knowledge hidden in these debates helps to investigate trends and opinions and to identify the cohesion of users when they deal with a specific topic. To this end, we propose a general multilayer network approach to investigate discussions on a social network. In order to prove the validity of our model, we apply it on a Twitter dataset containing tweets concerning opinions on COVID-19 vaccines. We extract a set of relevant hashtags (i.e., gold-standard hashtags) for each line of thought (i.e., pro-vaxxer, neutral, and anti-vaxxer). Then, thanks to our multilayer network model, we figure out that the anti-vaxxers tend to have ego networks denser (+14.39%) and more cohesive (+64.2%) than the ones of pro-vaxxer, which leads to a higher number of interactions among anti-vaxxers than pro-vaxxers (+393.89%). Finally, we report a comparison between our approach and one based on single networks analysis. We prove the effectiveness of our model to extract influencers having ego networks with more nodes (+40.46%), edges (+39.36%), and interactions with their neighbors (+28.56%) with respect to the other approach. As a result, these influential users are much more important to analyze and can provide more valuable information.     

Tsunami early warnings via Twitter in government: Net-savvy citizens' co-production of time-critical public information services

Governments aim to mitigate natural hazards' impacts through a disaster early warning system. Drawing on citizen co-production theory and resilient information infrastructures framework, we empirically examined government use of Twitter Tsunami Early Warning Civic Network and citizens' roles in co-providing timely and actionable information. The Indonesian government issued its tsunami early warning Tweet, which was “re-tweeted” without delay by its followers to their own followers to warn tsunami hazards during the 2012 earthquake. Within 15 min it reached over 4 million Twitter users. Based on our case study and social network analysis of Twitter information flows and exchanges within the network, we found that the speed and enormous reach of the government's Twitter tsunami early warnings would be significantly less without citizens' direct participation in re-tweeting, hence influencing greater control of the network. We present evidence for net-savvy citizens' co-production effects on increased government efficiency in providing time-critical public information services.     

Self‐report as an approach to measuring communication competence

Approaches to measurement of communication competence are reviewed. The self‐report approach to measurement of communication competence is examined. It is concluded that self‐reports have little validity as indicants of competent communicative performances but may serve as useful measures of self‐perceptions which may function as precursors of communicative choices. The Self‐Perceived Communication Competence scale is suggested as a measure which can he used for such purposes.     

On the Shoulders of Giants by Robert K. Merton. New York: Harcourt Brace Jovanovich,vicennial edition, 1985, 300 pp., hardcover.

Abstract

This article describes possibilities afforded by using social media, specifically Twitter, as a way to encourage students to join political conversations across the United States and around the world. In this study, we describe a project in which students used Twitter to share commentary about the state of the 2012 presidential election. The experiences of these students illustrate both the potential strengths and limitations of using social media as a tool for political engagement.     

Emotional Text Mining: Customer profiling in brand management

The widespread use of the Internet and the constant increase in users of social media platforms has made a large amount of textual data available. This represents a valuable source of information about the changes in people’s opinions and feelings. This paper presents the application of Emotional Text Mining (ETM) in the field of brand management. ETM is an unsupervised procedure aiming to profile social media users. It is based on a bottom-up approach to classify unstructured data for the identification of social media users’ representations and sentiments about a topic. It is a fast and simple procedure to extract meaningful information from a large collection of texts. As customer profiling is relevant for brand management, we illustrate a business application of ETM on Twitter messages concerning a well-known sportswear brand in order to show the potential of this procedure, highlighting the characteristics of Twitter user communities in terms of product preferences, representations, and sentiments.