scholarly journals Habitual Disclosure: Routine, Affordance, and the Ethics of Young Peoples Social Media Data Surveillance

2020 ◽  
Vol 6 (2) ◽  
pp. 205630512091561
Author(s):  
Clare Southerton ◽  
Emmeline Taylor
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Data Privacy ◽  
Qualitative Interviews ◽  
Photo Elicitation ◽  
Active Engagement ◽  
Social Media Data ◽  
Social Media Platforms ◽  
Data Surveillance ◽  
Media Data

Drawing on findings from qualitative interviews and photo elicitation, this article explores young people’s experiences of breaches of trust with social media platforms and how comfort is re-established despite continual violations. It provides rich qualitative accounts of users habitual relations with social media platforms. In particular, we seek to trace the process by which online affordances create conditions in which “sharing” is regarded as not only routine and benign but pleasurable. Rather it is the withholding of data that is abnormalized. This process has significant implications for the ethics of data collection by problematizing a focus on “consent” to data collection by social media platforms. Active engagement with social media, we argue, is premised on a tentative, temporary, shaky trust that is repeatedly ruptured and repaired. We seek to understand the process by which violations of privacy and trust in social media platforms are remediated by their users and rendered ordinary again through everyday habits. We argue that the processes by which users become comfortable with social media platforms, through these routines, call for an urgent reimagining of data privacy beyond the limited terms of consent.

scholarly journals Measuring Americans’ Comfort With Research Uses of Their Social Media Data

2021 ◽  
Vol 7 (3) ◽  
pp. 205630512110338
Author(s):  
Sarah Gilbert ◽  
Jessica Vitak ◽  
Katie Shilton
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Data Use ◽  
Data Types ◽  
Sensitive Data ◽  
Social Media Data ◽  
Content Type ◽  
Social Media Platforms ◽  
Diverse Data ◽  
Media Data

Research using online datasets from social media platforms continues to grow in prominence, but recent research suggests that platform users are sometimes uncomfortable with the ways their posts and content are used in research studies. While previous research has suggested that a variety of contextual variables may influence this discomfort, such factors have yet to be isolated and compared. In this article, we present results from a factorial vignette survey of American Facebook users. Findings reveal that researcher domain, content type, purpose of data use, and awareness of data collection all impact respondents’ comfort—measured via judgments of acceptability and concern—with diverse data uses. We provide guidance to researchers and ethics review boards about the ways that user reactions to research uses of their data can serve as a cue for identifying sensitive data types and uses.

scholarly journals How to address data privacy concerns when using social media data in conservation science

2021 ◽  
Author(s):  
Enrico Di Minin ◽  
Christoph Fink ◽  
Anna Hausmann ◽  
Jens Kremer ◽  
Ritwik Kulkarni
Keyword(s):  
Social Media ◽  
Data Privacy ◽  
Conservation Science ◽  
Social Media Data ◽  
Privacy Concerns ◽  
Address Data ◽  
Media Data

scholarly journals Embed2Detect: temporally clustered embedded words for event detection in social media

2021 ◽  
Author(s):  
Hansi Hettiarachchi ◽  
Mariam Adedoyin-Olowe ◽  
Jagdev Bhogal ◽  
Mohamed Medhat Gaber
Keyword(s):  
Social Media ◽  
Event Detection ◽  
High Volume ◽  
Detection Methods ◽  
Word Embeddings ◽  
Agglomerative Clustering ◽  
Data Set ◽  
Social Media Data ◽  
Social Media Platforms ◽  
Media Data

AbstractSocial media is becoming a primary medium to discuss what is happening around the world. Therefore, the data generated by social media platforms contain rich information which describes the ongoing events. Further, the timeliness associated with these data is capable of facilitating immediate insights. However, considering the dynamic nature and high volume of data production in social media data streams, it is impractical to filter the events manually and therefore, automated event detection mechanisms are invaluable to the community. Apart from a few notable exceptions, most previous research on automated event detection have focused only on statistical and syntactical features in data and lacked the involvement of underlying semantics which are important for effective information retrieval from text since they represent the connections between words and their meanings. In this paper, we propose a novel method termed Embed2Detect for event detection in social media by combining the characteristics in word embeddings and hierarchical agglomerative clustering. The adoption of word embeddings gives Embed2Detect the capability to incorporate powerful semantical features into event detection and overcome a major limitation inherent in previous approaches. We experimented our method on two recent real social media data sets which represent the sports and political domain and also compared the results to several state-of-the-art methods. The obtained results show that Embed2Detect is capable of effective and efficient event detection and it outperforms the recent event detection methods. For the sports data set, Embed2Detect achieved 27% higher F-measure than the best-performed baseline and for the political data set, it was an increase of 29%.

Google Plus as a Contentious Field of Revolutionary Identity

2021 ◽  
Vol 20 (3) ◽  
pp. 402-416
Author(s):  
Amirhossein Teimouri
Keyword(s):  
Social Media ◽  
Iranian Revolution ◽  
Social Media Data ◽  
Social Media Platforms ◽  
New Generation ◽  
Media Data

Abstract Social media platforms have been increasingly reinvigorating extreme movements, especially rightist movements. Utilizing unique Google Plus data, the author shows the rise and fall of the 2015 rightist anti-Nuclear Deal movement in Iran. He argues that the Google Plus platform in 2015 provided the new generation of revolutionary Islamist rightist activists with a contentious space of mobilization, enabling them to develop a new revolutionary rightist identity. This revolutionary identity and its corresponding language and discourse did not fully unfold in Iranian mainstream rightist media, even though rightist groups, compared to liberal groups, are not censored and repressed. The new generation of rightist activists perceived the Nuclear Deal as an existential threat to revolutionary principles of the country, and thus played out their outrage and identity anxieties on Google Plus. The author contends that this online outrage, due to the activists’ identity bond with the regime and the 1979 Iranian Revolution, however, did not translate into any massive offline mobilization against the Nuclear Deal. He also discusses the methodological implications of using social media data, especially the discontinuation of Google Plus.

Social Media-Based Data Collection and Analysis in Educational Research

2020 ◽  
pp. 54-77
Author(s):  
Liuli Huang
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Educational Research ◽  
Media In Education ◽  
Social Media Data ◽  
Educational Processes ◽  
Data Collection And Analysis ◽  
Media Data ◽  
Social Media In Education

The past decades have brought many changes to education, including the role of social media in education. Social media data offer educational researchers first-hand insights into educational processes. This is different from most traditional and often obtrusive data collection methods (e.g., interviews and surveys). Many researchers have explored the role of social media in education, such as the value of social media in the classroom, the relationship between academic achievement and social media. However, the role of social media in educational research, including data collection and analysis from social media, has been examined to a far lesser degree. This study seeks to discuss the potential of social media for educational research. The purpose of this chapter is to illustrate the process of collecting and analyzing social media data through a pilot study of current math educational conditions.

scholarly journals Review of Data Visualization for Social Media Postings

2018 ◽  
Vol 7 (4.38) ◽  
pp. 939
Author(s):  
Nur Atiqah Sia Abdullah ◽  
Hamizah Binti Anuar
Keyword(s):  
Social Media ◽  
Data Visualization ◽  
Line Graph ◽  
Data Types ◽  
Social Media Data ◽  
Data Analyst ◽  
The Social ◽  
Social Media Platforms ◽  
Types Of Information ◽  
Media Data

Facebook and Twitter are the most popular social media platforms among netizen. People are now more aggressive to express their opinions, perceptions, and emotions through social media platforms. These massive data provide great value for the data analyst to understand patterns and emotions related to a certain issue. Mining the data needs techniques and time, therefore data visualization becomes trending in representing these types of information. This paper aims to review data visualization studies that involved data from social media postings. Past literature used node-link diagram, node-link tree, directed graph, line graph, heatmap, and stream graph to represent the data collected from the social media platforms. An analysis by comparing the social media data types, representation, and data visualization techniques is carried out based on the previous studies. This paper critically discussed the comparison and provides a suggestion for the suitability of data visualization based on the type of social media data in hand.      

Social Media to Social Media Analytics

2019 ◽  
Vol 10 (2) ◽  
pp. 57-70 ◽  
Author(s):  
Vikas Kumar ◽  
Pooja Nanda
Keyword(s):  
Social Media ◽  
Social Media Analytics ◽  
Social Media Data ◽  
Ethical Concerns ◽  
Ethical Implications ◽  
The Social ◽  
Social Media Platforms ◽  
The Individual ◽  
The Impact ◽  
Media Data

With the amplification of social media platforms, the importance of social media analytics has exponentially increased for many brands and organizations across the world. Tracking and analyzing the social media data has been contributing as a success parameter for such organizations, however, the data is being poorly harnessed. Therefore, the ethical implications of social media analytics need to be identified and explored for both the organizations and targeted users of social media data. The present work is an exploratory study to identify the various techno-ethical concerns of social media engagement, as well as social media analytics. The impact of these concerns on the individuals, organizations, and society as a whole are discussed. Ethical engagement for the most common social media platforms has been outlined with a number of specific examples to understand the prominent techno-ethical concerns. Both the individual and organizational perspectives have been taken into account to identify the implications of social media analytics.

scholarly journals “It’s Not Like It’s Life or Death or Whatever”: Young People’s Understandings of Social Media Data

2018 ◽  
Vol 4 (3) ◽  
pp. 205630511878780 ◽  
Author(s):  
Luci Pangrazio ◽  
Neil Selwyn
Keyword(s):  
Social Media ◽  
Lived Experiences ◽  
Personal Data ◽  
Third Parties ◽  
Third Party ◽  
Cultural Issues ◽  
Social Media Data ◽  
Critical Data ◽  
Social Media Platforms ◽  
Media Data

Young people’s engagements with social media now generate large quantities of personal data, with “big social data” becoming an increasingly important “currency” in the digital economy. While using social media platforms is ostensibly “free,” users nevertheless “pay” for these services through their personal data—enabling advertisers, content developers, and other third parties to profile, predict, and position individuals. Such developments have prompted calls for social media users to adopt more informed and critical stances toward how and why their data are being used—that is, to build “critical data literacies.” This article reports on research that explores young social media users’ understandings of their personal data and its attendant issues. Drawing on research with groups of young people (aged 13–17 years), the article investigates the consequences of making third party (re)uses of personal data openly available for social media users to interpret and make critical sense of. The findings provide valuable insights into young people’s understandings of the technical, social, and cultural issues that underpin their ability to engage with, and make sense of, social media data. The article concludes by considering how research into critical data literacies might connect in more meaningful and effective ways with everyday lived experiences of social media use.

Analyzing Social Media Research: A Data Quality and Research Reproducibility Perspective

2021 ◽  
pp. 227797522110118
Author(s):  
Amit K. Srivastava ◽  
Rajhans Mishra
Keyword(s):  
Social Media ◽  
Data Quality ◽  
Quality Of Data ◽  
Social Media Data ◽  
National Crisis ◽  
Social Media Platforms ◽  
Quality Issues ◽  
The One ◽  
Media Data

Social media platforms have become very popular these days among individuals and organizations. On the one hand, organizations use social media as a potential tool to create awareness of their products among consumers, and on the other hand, social media data is useful to predict the national crisis, election polls, stock prediction, etc. However, nowadays, a debate is going on about the quality of data generated on social media platforms, whether it is relevant for prediction and generalization. The article discusses the relevance and quality of data obtained from social media in the context of research and development. Social media data quality issues may impact the generalizability and reproducibility of the results of the study. The paper explores possible reasons for quality issues in the data generated over social media platforms along with the suggestive measures to minimize them using the proposed social media data quality framework.

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