scholarly journals The Network Structure of Visited Locations According to Geotagged Social Media Photos

2017 ◽  
pp. 276-283 ◽  
Author(s):  
Christian Junker ◽  
Zaenal Akbar ◽  
Martí Cuquet
Keyword(s):  
Social Media ◽  
Network Structure

scholarly journals Network structure and patterns of information diversity on Twitter

2016 ◽  
Author(s):  
Jesse Conan Shore ◽  
Jiye Baek ◽  
Chrysanthos Dellarocas
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Cross Section ◽  
Network Structure ◽  
The Political ◽  
Cross Sectional ◽  
News Sources ◽  
Echo Chambers ◽  
Information Diversity

Social media have great potential to support diverse information sharing, but there is widespread concern that platforms like Twitter do not result in communication between those who hold contradictory viewpoints. Because users can choose whom to follow, prior research suggests that social media users exist in "echo chambers" or become polarized. We seek evidence of this in a complete cross section of hyperlinks posted on Twitter, using previously validated measures of the political slant of news sources to study information diversity. Contrary to prediction, we find that the average account posts links to more politically moderate news sources than the ones they receive in their own feed. However, members of a tiny network core do exhibit cross-sectional evidence of polarization and are responsible for the majority of tweets received overall due to their popularity and activity, which could explain the widespread perception of polarization on social media.

Multidimensional influencing factors of public opinion information dissemination in social media: Evidence from Weibo dataset

2019 ◽  
Vol 33 (31) ◽  
pp. 1950375 ◽  
Author(s):  
Guanghui Wang ◽  
Yufei Wang ◽  
Kaidi Liu ◽  
Jimei Li
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Information Content ◽  
Influencing Factors ◽  
Network Structure ◽  
Information Dissemination ◽  
Influential Factors ◽  
Channel Network ◽  
The Public ◽  
Information Characteristics

The factors influencing the dissemination of public opinion on social media, the main carrier of public opinion, are diverse, complex and changeable. Existing studies of influential factors of public opinion dissemination focus on the information itself and information sources in the dissemination process, failing to consider the comprehensive influence of multidimensional factors, such as information content, sources and channels. This study takes the identification of multidimensional influential factors of social media information dissemination as the research object and comprehensively sorts out the influencing factors of public opinion. To improve the scientific basis and accuracy of the research, multidimensional factors, including information characteristics, dissemination network structure and user-level attributes, are selected to analyze the effect of influential factors in different dimensions on the dissemination of social media public opinion information using econometric models. Three main conclusions of this paper are as follows: (1) The traditional information characteristics (information content) and information source attributes (user-level factor) are not the only key factors affecting information dissemination, while the information channel (network structure) is worth more consideration. (2) Netizens tend to pay more attention to the psychological and emotional attributes of information when forwarding public opinions. The communication mode in which offline social elites enlighten the public no longer exists; whether a user is a network celebrity or lives in the central area no longer significantly affects public opinion dissemination. (3) The higher the total amount of information users release, the more the information would interfere with the public opinion. This is mainly because users with a higher level of activity may release more invalid information about advertising that has nothing to do with public opinion events.

INFORMATION EXCHANGES OF SOCIAL MEDIA EVANGELISTS DURING FLOOD: A SOCIAL NETWORK ANALYSIS

2016 ◽  
Vol 78 (9-3) ◽  
Author(s):  
Abdus-samad Temitope Olanrewaju ◽  
Rahayu Ahmad ◽  
Kamarul Faizal Hashim
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Information Dissemination ◽  
Network Structures ◽  
Analysis Technique ◽  
Types Of Information ◽  
Information Brokers

Information dissemination during disaster is very crucial, but inherits several complexities associated with the dynamic characteristics of the disaster. Social media evangelists (activists) play an important role in disseminating critical updates at on-site locations. However, there is limited understanding on the network structure formed and its evolution and the types of information shared. To address these questions, this study employs Social Network Analysis technique on a dataset containing 157 social media posts from an influential civilian fan page during Malaysia’s flood. The finding demonstrates three different network structures emerged during the flood period. The network structure evolves depending on the current state of the flood, the amount of information available and the need of information. Through content analysis, there were seven types of information exchanges discovered. These information exchanges evolved as the scale and magnitude of flood changes. In conclusion, this study shows the emergence of different network structures, density and identification of influential information brokers among civilians that use social media during disaster. Despite the low number of influential information brokers, they successfully manage their specific cluster in conveying information about the disaster and most importantly coordinating the rescue mission.

Are you passing along something true or false? Dissemination of social media messages about genetically modified organisms

2020 ◽  
pp. 096366252096674
Author(s):  
Qian Xu ◽  
Yunya Song ◽  
Nan Yu ◽  
Shi Chen
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Structural Stability ◽  
Network Structure ◽  
Genetically Modified Organisms ◽  
Genetically Modified ◽  
Network Density ◽  
Media Messages ◽  
Practical Implications

Using network analysis, this study investigates how information veracity and account verification influence the dissemination of information in the context of discourse about genetically modified organisms on social media. We discovered that misinformation and true information about genetically modified organisms demonstrated different dissemination patterns on social media. In general, the dissemination networks of misinformation about genetically modified organisms were found to have higher structural stability than those of true information about genetically modified organisms, as shown by the denser network structure with fewer distinct subgroups residing within the dissemination networks. More importantly, unverified account status significantly boosted the dissemination of misinformation by increasing network density. In addition, we found that the posts about genetically modified organisms from unverified accounts received more reposts and had more layers of information relay than those from the verified accounts. Theoretical and practical implications of these findings on combating misinformation are discussed in the article.

Beyond the power of networks: Differentiating network structure from social media affordances for perceived social support

2016 ◽  
Vol 19 (6) ◽  
pp. 861-879 ◽  
Author(s):  
Weixu Lu ◽  
Keith N Hampton
Keyword(s):  
Social Support ◽  
Social Media ◽  
Social Network ◽  
Network Structure ◽  
Emotional Support ◽  
Positive Association ◽  
Network Size ◽  
Perceived Support ◽  
Social Network Structure ◽  
The Relationship

Existing research suggests that social media use is associated with higher levels of social capital—the resources contained within a person’s network of friends, family, and other acquaintances. However, in predicting access to these resources, it has been impossible to distinguish the affordances of social media from the underlying advantage of maintaining a favorable social network of relationships on- and offline. Based on data from a representative, national survey, we compare the relationship between social network structure and various activities on Facebook for one type of resource: informal social support in the form of companionship, emotional support, and tangible aid. In addition to a positive association between number of close ties, overall network size and diversity and social support, we find that Facebook status updates and private messaging are independently associated with perceived support. We argue that these affordances are an outcome of the “pervasive awareness” provided by social media.

scholarly journals Online Conversation Analysis as The Research Method of Social Media Texts: Rationale, Steps and Example

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Aurelius R.L. Teluma
Keyword(s):  
Social Media ◽  
Conversation Analysis ◽  
Network Structure ◽  
Research Method ◽  
Important Research ◽  
Social Media Text ◽  
Media Texts ◽  
Main Components ◽  
Online Conversation ◽  
Identity Problems

The main components of social media text are the language and network structure of users. Virtually, social media texts appear in the form of posts and comments. Therefore, social media texts have the characteristics of online conversation. So, online conversation analysis (OCA) is one of the important research methodologies for reviewing social media texts. This paper aims to provide a rationale, steps, and examples of online conversation analysis practices. The most important aspect of the conversation is conversational coherence, namely the connection and meaningfulness in conversation. However, asynchronous factors, information abundance and identity problems in social media texts make such analysis require a number of additional steps. The steps for analyzing online conversations include these aspects: turn taking structures, construction of exchanges, parts-alliances-talks, trouble and repair, preferences and accountability, institutional category and identity. Keywords: online conversation analysis; social media text; research method

scholarly journals Fat-Burning or Fat-Shaming? Theme and Community Overlap Between Online, Weight-Stigmatizing and Exercise-Promoting Networks.

2021 ◽  
Author(s):  
Ahuitz Rojas-Sánchez ◽  
Jenine K. Harris ◽  
Philippe Sarrazin ◽  
Aïna Chalabaev
Keyword(s):  
Social Media ◽  
Weight Loss ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Network Structure ◽  
Path Length ◽  
Average Path Length ◽  
Common Word ◽  
Total Degree

Abstract Purpose: This study aimed to determine if networks of users consistently posting about exercise and fat exist and overlap on social media sites.Method: We collected 3,772,507 posts from Twitter that included the words “fat” and “exercise”. Using network structure methods, we identified communities of interconnected users and overlaps between those tweeting “fat” and those tweeting “exercise”. Results: Common word pairings were identified using Natural Language Processing (NLP). Networks of users consistently talking about exercise (n=3,573) and fat (n=2,007) were found on Twitter. An increased mean total-degree and reduced average path length indicate that the fitness-talk network serves as a connecting bridge between highly scattered communities of the weight-talk network. Conclusion: We identified groups on Twitter dedicated to consistently producing weight stigmatizing content and promoting exercise with weight-loss messages. These groups partially overlap with pro-health groups which could lead to users looking for exercise advice in Twitter to find themselves immersed in a stigmatizing network.

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