scholarly journals CHALLENGING SPATIAL MARGINALIZATION THROUGH SOCIAL MEDIA COMMUNICATION? A CASE STUDY OF THE TWITTER DISCOURSE ON HOUSING IN BERLIN

2020 ◽  
Author(s):  
Daniela Stoltenberg
Keyword(s):  
Social Media ◽  
Social Stratification ◽  
Public Discourse ◽  
Social Power ◽  
Spatial Inequality ◽  
Future Research ◽  
Power Structures ◽  
Media Communication ◽  
Urban Issues ◽  
Social Media Communication

Urban public life has historically and famously been structured by social stratification and a segregation of social milieus. Such spatialized social inequality along the lines of, most importantly, class, age, and ethnicity engenders unequal access to civic participation and supportive social networks. Meanwhile, the Internet and Web 2.0 technologies in particular have often been hailed for their potential of bringing underrepresented voices into the public discourse and even creating so-called “networked counterpublics”, challenging social power structures. This contribution seeks to address the question of whether social media communication about urban issues challenges or reproduces patterns of spatial inequality in its attention distribution. Empirically, it investigates the distribution of place-naming within the Berlin-based Twitter discourse on housing. It finds that - while issue attention in the urban Twitter discourse is clearly spatially unequal, with a striking imbalance between center and periphery - neither sociodemographic composition nor issue characteristics perform well in explaining these patterns. Instead it proposes focusing more on local civic and activist infrastructure in future research.

scholarly journals Emoji Identification and Prediction in Hebrew Political Corpus

10.28945/4346 ◽  
2019 ◽  
Keyword(s):  
Social Media ◽  
Text Message ◽  
Supervised Machine Learning ◽  
Future Research ◽  
Media Communication ◽  
Prediction Task ◽  
Morphologically Rich Languages ◽  
Definition Of ◽  
Textual Content ◽  
Social Media Communication

[This Proceedings paper was revised and published in the 2019 issue of the journal Issues in Informing Science and Information Technology, Volume 16] Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identification is the complementary preceding task of determining if a given text message includes emojies. Methodology: We adopt a supervised Machine Learning (ML) approach. We compare two text representation approaches, i.e., n-grams and character n-grams and analyze the contribution of additional metadata features to the classification. Contribution: The task of emoji identification is novel. We extend the definition of the emoji prediction task by allowing to use not only the textual content but also meta-data analysis. Findings: Metadata improve the classification accuracy in the task of emoji identification. In the task of emoji prediction it is better to apply feature selection. Recommendations for Practitioners: In many of the cases the classifier decision seems fitter to the comment con-tent than the emoji that was chosen by the commentator. The classifier may be useful for emoji suggestion. Recommendations for Researchers: Explore character-based representations rather than word-based representations in the case of morphologically rich languages. Impact on Society: Improve the modeling of social media communication. Future Research: We plan to address the multi-label setting of the emoji prediction task and to investigate the deep learning approach for both of our classification tasks.

User and Firm Generated Content on Online Social Media

2016 ◽  
Vol 6 (3) ◽  
pp. 34-49 ◽  
Author(s):  
Abhinita Daiya ◽  
Subhadip Roy
Keyword(s):  
Social Media ◽  
Levels Of Analysis ◽  
Future Research ◽  
Media Content ◽  
Media Communication ◽  
Communication Content ◽  
Online Social Media ◽  
Research Questions ◽  
Social Media Communication ◽  
Level Of Analysis

Social media communication content has gained a lot of interest in e-commerce literature. The present research note explores the scope of social media communication content across content source and levels of analysis. Based on a comprehensive review of 36 empirical papers spanning a decade (2004-2016), the research in social media content source is divided as user generated and firm generated. The levels of analysis are divided into three groups: users and society, platforms and intermediaries and firms and industries. Subsequently, a grid with six cells is created that has the content source (user/firm) on one axis and level of analysis on the other. The findings reveal communication content across users and society to be the most researched area, whereas, platforms and intermediaries being the least researched. Further, a set of future research questions are proposed for content in social media across various levels of analysis.

Social media: communication strategies, engagement and future research directions

2017 ◽  
Vol 29 (1) ◽  
pp. 2-19 ◽  
Author(s):  
Rebecca Dolan ◽  
Jodie Conduit ◽  
John Fahy ◽  
Steve Goodman
Keyword(s):  
Social Media ◽  
Research Agenda ◽  
Communication Strategies ◽  
Customer Engagement ◽  
Future Research ◽  
Media Communication ◽  
Content Type ◽  
Future Research Agenda ◽  
Social Media Communication ◽  
The Impact

Purpose This study aims to use social media data to identify brand communication strategies on Facebook. The analysis uncovers trends and statistics regarding engagement rates. This research leads to the development of a future research agenda for social media and engagement research. Design/methodology/approach The Facebook Insights data of 12 wine brands over a 12-month period informed this study. Descriptive analysis was undertaken to examine the social media communication strategies of these brands. The impact of these strategies on engagement metrics is also examined. Findings The findings demonstrate a low rate of engagement among the users of the wine brand Facebook pages. A majority of Facebook fans rarely engage with the brands. The results demonstrate that user engagement varies depending on the day of the week and hour of the day of the brand post. Practical implications Wine brands can use these findings as a guideline for effective practice and as a benchmarking tool for assessing their social media performance. The paper provides implications for marketing scholars through the development of a future research agenda related to social media, customer engagement and wine marketing. Originality/value This paper fulfils an identified need by offering practical advice to wine producers on the necessity to explore and understand social media strategy and customer engagement characteristics.

scholarly journals When Nobody “Likes” You: Perceived Ostracism Through Paralinguistic Digital Affordances Within Social Media

2018 ◽  
Vol 4 (3) ◽  
pp. 205630511880030 ◽  
Author(s):  
Rebecca A. Hayes ◽  
Eric D. Wesselmann ◽  
Caleb T. Carr
Keyword(s):  
Social Media ◽  
Social Interaction ◽  
Communication Channels ◽  
Psychological Effects ◽  
Future Research ◽  
Media Content ◽  
Media Communication ◽  
Social Media Platforms ◽  
The One ◽  
Social Media Communication

This research explores the processes of perceived ostracism ensuing from a lack of feedback via paralinguistic digital affordances (PDAs), the one-click tools (e.g., Likes and +1s) which are one of the most used features of social media, provided to an individual’s posted social media content. The positive and negative psychological outcomes of social media communication have been well-documented. However, as social media have become entrenched as some of our most common communication channels, the absence of communication via social media has been underexplored and may have negative psychological and communicative outcomes. We utilized focus groups ( N = 37) to examine perceptions of ostracism when individuals did not receive PDAs to their posted content across social media platforms. Participants reported feeling excluded only when they did not receive PDAs from select relationally close or socially superior network members, suggesting audience targeting and expectations when posting. Users frequently attributed low PDA counts to system and content factors. These results contribute to a developing understanding of the psychological effects of lack of communication via social media and provide insight for future research, demonstrating that social exclusion may not manifest from a complete lack of social interaction but rather may occur when individuals do not receive expected or desired feedback.

scholarly journals Emoji Identification and Prediction in Hebrew Political Corpus

10.28945/4372 ◽  
2019 ◽  
Vol 16 ◽  
pp. 343-359
Author(s):  
Chaya Liebeskind
Keyword(s):  
Social Media ◽  
Text Message ◽  
Supervised Machine Learning ◽  
Future Research ◽  
Media Communication ◽  
Prediction Task ◽  
Morphologically Rich Languages ◽  
Definition Of ◽  
Textual Content ◽  
Social Media Communication

Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identification is the complementary preceding task of determining if a given text message includes emojies. Methodology: We adopt a supervised Machine Learning (ML) approach. We compare two text representation approaches, i.e., n-grams and character n-grams and analyze the contribution of additional metadata features to the classification. Contribution: The task of emoji identification is novel. We extend the definition of the emoji prediction task by allowing to use not only the textual content but also meta-data analysis. Findings: Metadata improve the classification accuracy in the task of emoji identification. In the task of emoji prediction it is better to apply feature selection. Recommendations for Practitioners: In many of the cases the classifier decision seems fitter to the comment content than the emoji that was chosen by the commentator. The classifier may be useful for emoji suggestion. Recommendation for Researchers: Explore character-based representations rather than word-based representations in the case of morphologically rich languages. Impact on Society: Improve the modeling of social media communication. Future Research: We plan to address the multi-label setting of the emoji prediction task and to investigate the deep learning approach for both of our classification tasks

STRATEGI KOMUNIKASI CROWDFUNDING PADA KOLASE.COM

2019 ◽  
Vol 2 (2) ◽  
pp. 177-187
Author(s):  
Venessa Agusta Gogali ◽  
Fajar Muharam ◽  
Syarif Fitri
Keyword(s):  
Social Media ◽  
Communication Strategies ◽  
Communication Strategy ◽  
New Method ◽  
Media Communication ◽  
Social Activists ◽  
Social Media Communication

Crowdfunding is a new method in fundraising activities based online. Moreover, the level of penetration of social media to the community is increasingly high. This makes social activists and academics realize that it is important to study social media communication strategies in crowdfunding activities. There is encouragement to provide an overview of crowdfunding activities. So the author conducted a research on "Crowdfunding Communication Strategy Through Kolase.com Through Case Study on the #BikinNyata Program Through the Kolase.com Website that successfully achieved the target. Keywords: Strategic of Communication, Crowdfunding, Social Media.

#INCLUSION – THE IMPACT OF SOCIAL MEDIA COMMUNICATION ON THE LEGITIMACY OF ARMED FORCES

2019 ◽  
pp. 43-60
Author(s):  
EVA MOEHLECKE DE BASEGGIO ◽  
OLIVIA SCHNEIDER ◽  
TIBOR SZVIRCSEV TRESCH
Keyword(s):  
Social Media ◽  
Political Communication ◽  
Structural Equation ◽  
Armed Forces ◽  
Equation Model ◽  
Media Communication ◽  
The Public ◽  
Political Legitimation ◽  
Social Media Communication ◽  
The Impact

The Swiss Armed Forces (SAF), as part of a democratic system, depends on legitimacy. Democracy, legitimacy and the public are closely connected. In the public sphere the SAF need to be visible; it is where they are controlled and legitimated by the citizens, as part of a deliberative discussion in which political decisions are communicatively negotiated. Considering this, the meaning of political communication, including the SAF’s communication, becomes obvious as it forms the most important basis for political legitimation processes. Social media provide a new way for the SAF to communicate and interact directly with the population. The SAF’s social media communication potentially brings it closer to the people and engages them in a dialogue. The SAF can become more transparent and social media communication may increase its reputation and legitimacy. To measure the effects of social media communication, a survey of the Swiss internet population was conducted. Based on this data, a structural equation model was defined, the effects of which substantiate the assumption that the SAF benefits from being on social media in terms of broadening its reach and increasing legitimacy values.

scholarly journals Patient Care, Information, Communication and Social Media Influencing Bias—A Discourse

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 28
Author(s):  
Paula M. Procter
Keyword(s):  
Social Media ◽  
Patient Care ◽  
Information Communication ◽  
Media Communication ◽  
Care Information ◽  
Social Media Communication ◽  
Society Today ◽  
Selection Of

Misinformation and disinformation are prevalent across society today, their rise to prominence developed mainly through the expansion of social media. Communication has always been recognised in health and care settings as the most important element between people who are receiving care and those delivering, managing, and evaluating care. This paper, through a discourse approach, will explore communication through the perception of information formed following personal selection of influencers and try to determine how such affects patient care.

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