GERAKAN SOSIAL BARU INDONESIA: STUDI GERAKAN GEJAYAN MEMANGGIL 2019

The Gejayan Calling Movement 2019 becomes an interesting phenomenon of the development of new student social movements in Indonesia. Using social media platforms (#tranding topics) as a means of mass mobilization, this action succeeded in managed around 15,000 protesters. This article aims to elaborate the 2019 Gejayan Menanggil Movement in more detail, covering the background of the action, the means of mass mobilization, the consolidation process, and the issues raised. The research method uses a qualitative approach with data collection techniques through virtual observations on social media, data searches on the Drone Emprit website, and in-depth interviews with members of HMI DIPO, HMI MPO, IMM, GMNI, and ARB (Aliansi Rakyat Bergerak). The collected data were analyzed using NVivo Plus software. The results show that the Gejayan Calling Movement has become the starting point for changes in social movements in Indonesia, where the foundations built are no longer based on material resistance, but are more based on issues of humanity, injustice, politics, the environment and women. Therefore, the ideology of the movements has also changed from a class resistance to an identity resistance.Gerakan Gejayan Memanggil 2019 menjadi salah satu fenomena menarik dari perkembangan gerakan sosial baru mahasiswa di Indonesia. Melalui platform media sosial (tranding topic) sebagai alat mobilisasi massa, aksi ini telah melibatkan 15.000 (lima belas ribu) demonstran. Artikel ini bermaksud untuk mengelaborasi Gerakan Gejayan Memanggil 2019 secara lebih mendalam, meliputi latar belakang aksi, sarana mobilisasi massa, proses konsolidasi, dan isu yang diangkat. Metode penelitian menggunakan pendekatan kualitatif dengan teknik pengumpulan data melalui observasi virtual di sosial media, penelusuran data di situs internet Drone Emprit, dan wawancara mendalam terhadap anggota HMI DIPO, HMI MPO, IMM, GMNI, dan ARB (Aliansi Rakyat Bergerak). Data yang terkumpul dianalisis dengan menggunakan software NVivo Plus. Hasil penelitian menunjukkan bahwa Gerakan Gejayan Memanggil ini telah menjadi titik tolak perubahan gerakan sosial di Indonesia, dimana pondasi yang dibangun tidak lagi berbasis pada perlawanan yang bersifat material, tetapi lebih berbasiskan pada isu-isu kemanusiaan, ketidakadilan, politik, lingkungan dan perempuan. Oleh sebab itu, ideologi yang berkembang berubah dari hal yang bersifat perlawanan kelas menjadi perlawanan identitas.

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The Nested Precarities of Creative Labor on Social Media

Social Media + Society ◽

10.1177/20563051211021368 ◽

2021 ◽

Vol 7 (2) ◽

pp. 205630512110213

Author(s):

Brooke Erin Duffy ◽

Annika Pinch ◽

Shruti Sannon ◽

Megan Sawey

Keyword(s):

Social Media ◽

Cultural Production ◽

Ecological Model ◽

Creative Economy ◽

Cultural Industries ◽

Professional Success ◽

Social Media Platforms ◽

The Media ◽

Depth Interviews

While metrics have long played an important, albeit fraught, role in the media and cultural industries, quantified indices of online visibility—likes, favorites, subscribers, and shares—have been indelibly cast as routes to professional success and status in the digital creative economy. Against this backdrop, this study sought to examine how creative laborers’ pursuit of social media visibility impacts their processes and products. Drawing upon in-depth interviews with 30 aspiring and professional content creators on a range of social media platforms—Instagram, YouTube, TikTok, Pinterest, and Twitter—we contend that their experiences are not only shaped by the promise of visibility, but also by its precarity. As such, we present a framework for assessing the volatile nature of visibility in platformized creative labor, which includes unpredictability across three levels: (1) markets, (2) industries, and (3) platform features and algorithms. After mapping out this ecological model of the nested precarities of visibility, we conclude by addressing both continuities with—and departures from—the earlier modes of instability that characterized cultural production, with a focus on the guiding logic of platform capitalism.

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Social Media and Emotional Well-being: Pursuit of Happiness or Pleasure

Asia Pacific Media Educator ◽

10.1177/1326365x211003737 ◽

2021 ◽

pp. 1326365X2110037

Author(s):

D. Guna Graciyal ◽

Deepa Viswam

Keyword(s):

Social Media ◽

Social Networking ◽

Virtual World ◽

Mixed Methods Research ◽

Well Being ◽

Pursuit Of Happiness ◽

Social Dysfunction ◽

Combining Data ◽

Social Media Platforms ◽

Depth Interviews

Virtual engagement of lives has been made possible with the advent of social media. Almost 80% of the day are spent virtually on Facebook, Instagram, Twitter, YouTube, Snapchat, etc. Usage of social media to connect to and communicate with the ones we care about is always healthy, termed as social networking. Social dysfunction occurs when the constant communication leads to the point where our real or offline life gets replaced by virtual or online life. There is a slight boundary between social networking and social dysfunction. When social networking is advantageous, social dysfunction affects emotional well-being. When emotional well-being is affected, many users experience a compulsion to dissociate from the real world as they find virtual world, full of fantasy and enjoyment. When the Internet was created, perhaps no one was aware of its potential. More than the convenience for sharing of information it has brought the world so close to crumbling the geographical boundaries. The more people-to-people communication is, the more is the strengthening of relationships, bonds grow stronger with ‘more’ social media platforms. Being on ‘more’ social media platforms has become a benchmark for living amidst the younger generation. Either as an activity of happiness or as an activity of pleasure, users tend to use social media at varying levels. This paper aims to conceptualize the the intricacies of social media in young lives and to discern whether their association is happiness or pleasure activity. The research method of this paper has a mixed-methods research design combining data from structured survey with information outputs from in-depth interviews.

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Explaining Donation Behavior in Medical Crowdfunding in Social Media

SAGE Open ◽

10.1177/21582440211014520 ◽

2021 ◽

Vol 11 (2) ◽

pp. 215824402110145

Author(s):

Zhengwei Huang ◽

Jing Ouyang ◽

Xiaohong Huang ◽

Yanni Yang ◽

Ling Lin

Keyword(s):

Social Media ◽

Interpersonal Relationship ◽

Elaboration Likelihood ◽

Perceived Trust ◽

Likelihood Model ◽

Social Media Platforms ◽

Perceived Behavior Control ◽

Donation Behavior ◽

Depth Interviews ◽

Social Media Network

Medical crowdfunding in social media is growing to be a convenient, accessible, and secure manner to cover medical expenses. It differs from traditional donation initiatives and medical crowdfunding on non-social media platforms in that projects are disseminated via social media network and among acquaintances. Through semi-structured in-depth interviews on donation behaviors of 52 respondents, this study uses grounded theory to extract seven main categories that affect medical crowdfunding donation behavior in social media, namely interpersonal relationship, reciprocity of helping, attitude toward donation, perceived behavior control, perceived trust, project information, and characteristics of patients. In the spirit of Elaboration Likelihood Model, we develop a theoretical framework that the seven factors influence donation behavior in medical crowdfunding in social media via a central and a peripheral route.

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

Machine Learning ◽

10.1007/s10994-021-05988-7 ◽

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%.

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Google Plus as a Contentious Field of Revolutionary Identity

Comparative Sociology ◽

10.1163/15691330-bja10036 ◽

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.

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IMPACT OF SOCIAL MEDIA ON SALES FUNNELS IN B2C AND B2B SEGMENTS IN THE REPUBLIC OF NORTH MACEDONIA

Зборник радова Економског факултета у Источном Сарајеву ◽

10.7251/zrefis2122051k ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Martin Kiselicki ◽

Saso Josimovski ◽

Lidija Pulevska Ivanovska ◽

Mijalce Santa

Keyword(s):

Social Media ◽

New Technologies ◽

Secondary Data ◽

Primary Data ◽

World Population ◽

Social Media Platforms ◽

The Republic ◽

New Generation ◽

Sales Funnel ◽

Media Data

The research focuses on introducing social media platforms as either a complementary or main channel in the company sales funnel. Internet technologies and Web 2.0 continue to provide innovations in digital marketing, with the latest iteration being lead generation services through social media. Data shows that almost half of the world population is active on social media, with the new Generation Alpha being projected to be entirely online dependent and proficient in the use of new technologies. The paper provides an overview of the digitalization of sales funnels, as well as the benefits that social media platforms can offer if implemented correctly. Secondary data provides the basis for transforming sales funnels with social media, where previous research provides limited data on the effectiveness of these types of efforts. Primary data demonstrates that introducing social media platforms can provide improvements of up to 3 to 4 times in analyzed case studies, as well as the shorter time when deciding about purchase in use case scenarios. Social media advertising can also be utilized to shorten the sales funnel process and serve as a unified point of entrance and exit in the first few stages.

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Sensing And Detecting Small-Scale Events Using Geosocial Media Data

10.32920/16834420 ◽

2021 ◽

Author(s):

Shishuo Xu

Keyword(s):

Social Media ◽

Event Detection ◽

Human Movement ◽

Small Scale ◽

Type I ◽

Social Event ◽

Ground Truth Data ◽

Social Events ◽

Social Media Platforms ◽

Media Data

<div>Small-scale events involve interactive human movement in limited space and time. Social media platforms possibly generate large amount of geospatially-referenced information related to small-scale events. It benefits individuals, management departments, and urban systems if small-scale events can be timely detected from social media platforms, where measuring the abnormal patterns of human movement to discover events and analyzing associated texts to interpret the reasons behind abnormal movement are two keys. Through investigating how people move as different events occur and measuring the patterns on social media platforms, small-scale events can be generally classified into two types, namely type I events with abrupt patterns and type II events with random occurrence of key factors, where social events and traffic events are representative correspondingly.</div><div>Despite many studies have been conducted to detect social events and traffic events using geosocial media data, there still are some un-answered questions requiring further research. Most existing studies did not identify occurring events from a full coverage of spatial, temporal, and semantic perspectives. Studies concerning social event detection lack efficient semantic analysis summarizing event content to infer the reasons driving the abnormal movement. The typical classification-based method regarding traffic event detection lacks investigation on how the spatiotemporal distribution of traffic relevant posts associate with the occurring traffic events, and simply assigns the detected events with predefined categories, missing events that indicate traffic anomalies but go beyond the predetermined categories.<br></div><div>In this thesis, spatial-temporal-semantic approaches are proposed to measure spatiotemporal patterns of posts and users of social media platforms to capture abnormal human movement, and analyze the content of associated posts to mine the reasons driving the movement. A variety of techniques including machine learning, natural language processing, and spatiotemporal analysis are adopted to realize effective detection. Based on one-year Twitter data collected in Toronto, 2014 Toronto International Film Festival and traffic anomaly detection are selected as two case studies to evaluate the performance of proposed approaches. Through comparing with the ground truth data, the result reveals that more than 80% of the detected events do refer to real-world events, which illustrates the feasibility and efficiency of proposed approaches.<br></div><div><br></div><div>Keywords: Small-scale event, Event detection, Geosocial media data, Traffic event, Social event, Twitter, Spatiotemporal clustering<br></div>

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Outro

Renegades ◽

10.1093/oso/9780197577677.003.0008 ◽

2021 ◽

pp. 123-128

Author(s):

Trevor Boffone

Keyword(s):

Social Media ◽

Social Movements ◽

Social Justice ◽

Significant Role ◽

Black Girls ◽

New Music ◽

Black Lives Matter ◽

Social Media Platforms ◽

The Revolution

The Outro explores how the Renegades throughout this book used their social media platforms and clout to further social justice messages during the height of the renewed Black Lives Matter movement following the murder of George Floyd in summer 2020. Renegade Zoomers played a significant role in celebrating Blackness and made many of these “moves” on social media. Whether it was through attending marches, creating viral dance challenges, or producing new music, Renegades positioned their creativity, joy, and labor as central to the movement for Black lives. Their work forced onlookers, moreover, to recognize the labor of Black girls in our social movements. Renegades reveal, ultimately, that the revolution will be digital.

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Mining social media data to investigate patient perceptions regarding DMARD pharmacotherapy for rheumatoid arthritis

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-217333 ◽

2020 ◽

Vol 79 (11) ◽

pp. 1432-1437 ◽

Cited By ~ 1

Author(s):

Chanakya Sharma ◽

Samuel Whittle ◽

Pari Delir Haghighi ◽

Frada Burstein ◽

Roee Sa'adon ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Social Media ◽

Side Effects ◽

Sentiment Analysis ◽

Computer Algorithms ◽

Social Media Platforms ◽

Synthetic Agents ◽

Positive Sentiment ◽

Negative Sentiment ◽

Media Data

ObjectivesWe hypothesise that patients have a positive sentiment regarding biological/targeted synthetic disease modifying anti-rheumatic drugs (b/tsDMARDs) and a negative sentiment towards conventional synthetic agents (csDMARDs). We analysed discussions on social media platforms regarding DMARDs to understand the collective sentiment expressed towards these medications.MethodsTreato analytics were used to download all available posts on social media about DMARDs in the context of rheumatoid arthritis. Strict filters ensured that user generated content was downloaded. The sentiment (positive or negative) expressed in these posts was analysed for each DMARD using sentiment analysis. We also analysed the reason(s) for this sentiment for each DMARD, looking specifically at efficacy and side effects.ResultsComputer algorithms analysed millions of social media posts and included 54 742 posts about DMARDs. We found that both classes had an overall positive sentiment. The ratio of positive to negative posts was higher for b/tsDMARDs (1.210) than for csDMARDs (1.048). Efficacy was the most commonly mentioned reason in posts with a positive sentiment and lack of efficacy was the most commonly mentioned reason for a negative sentiment. These were followed by the presence/absence of side effects in negative or positive posts, respectively.ConclusionsPublic opinion on social media is generally positive about DMARDs. Lack of efficacy followed by side effects were the most common themes in posts with a negative sentiment. There are clear reasons why a DMARD generates a positive or negative sentiment, as the sentiment analysis technology becomes more refined, targeted studies could be done to analyse these reasons and allow clinicians to tailor DMARDs to match patient needs.

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Review of Data Visualization for Social Media Postings

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.38.27613 ◽

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.

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