Social Media Research Research Articles

Social Media in Research on a Marginalized Identity: The Case of Atheism in Indonesia

Social media have played a major role as a place where one can meet and socialize with like-minded people, and this is especially important for marginalized groups. Atheists depict such a group in Indonesia where public expressions of atheism are punishable. Whereas social media often plays an important role in finding like-minded people, it is also potentially dangerous to reject religion on social media. In this research workshop, I argue that insights into the ways in which atheists use and engage in social media groups are crucial if one wants to know more about atheist ways of life in Indonesia. However, atheist groups are subject to internal fragmentation, as atheism in Indonesia is highly diverse, and, as a researcher, one can find oneself caught up in these internal struggles. Finally, I argue that social media research is an important addition to offline research, since it enables the researcher, especially when dealing with sensitive issues and identities, to directly enter and critically engage with the premises in which such identities are constituted and developed.

Lots of bots or maybe nots: A process for detecting bots in social media research

The use of bot messaging, that being artificially created messages, has increased since 2010. While not all bots are bad, many have been used to share extreme and divisive views on a range of topics, from policy discussion to brand electronic word of mouth. The issue with bot messaging and its prevalence is that it can affect researchers’ understanding of a topic. For example, if 25% of a dataset is fabricated, decision-making may result in a loss of profit or poor policy formation. To counteract the use of bots, this research note offers a framework to alleviate the potentially destructive nature of bot data and ensure the cleaning of data is thorough and beneficial to decision-making based on social media commentary. The framework is a four-step process, which includes thematic, automated, and characteristic identification stages. We provide three case studies to demonstrate the approach and conclude by providing key practical implications.

How marketer-generated content characteristics affect consumer engagement? Empirical evidence from China's WeChat food marketing

Purpose Leveraging marketer-generated content (MGC) can increase firms' success. However, few studies uncover the effects of MGC-related attributes on consumer engagement in the context of food marketing. This paper aims to explore the influence of MGC characteristics (valence, content types, vividness and interactivity) on consumer engagement.Design/methodology/approachThis study uses WeChat official account data of seven food companies from China and conducts negative binomial regression models.FindingsThe findings indicate that different MGC-related characteristics have separate impacts on consumer WeChat engagement. Title valence, transactional title content and title with punctuation vividness negatively affect consumers' consuming engagement. Knowledgeable or entertaining title content and title with interactivity both positively affect consumers' consuming engagement. Moreover, transactional body text content negatively influences consumers' contributing engagement, whereas entertaining body text content shows positive effects. Vivid and interactive MGC body text attributes enhance consumers' contributing engagement behavior.Originality/value This study contributes to social media research in food marketplaces and sheds light on the effect of different WeChat MGC characteristics on separate consumer engagement.

Detecting Spam Bots on Social Network

Bots have made an appearance on social media in a variety of ways. Twitter, for instance, has been particularly hard hit, with bots accounting for a shockingly large number of its users. These bots are used for nefarious purposes such as disseminating false information about politicians and inflating celebrity expectations. Furthermore, these bots have the potential to skew the results of conventional social media research. With the multiple increases in the size, speed, and style of user knowledge in online social networks, new methods of grouping and evaluating such massive knowledge are being explored. Getting rid of malicious social bots from a social media site is crucial. The most widely used methods for identifying fraudulent social bots focus on the quantitative measures of their actions. Social bots simply mimic these choices, leading to a low level of study accuracy. Transformation clickstream sequences and semi-supervised clustering were used to develop a new technique for detecting malicious social bots. This method considers not only the probability of user activity clickstreams being moved, but also the behavior's time characteristic. The detection accuracy for various kinds of malware social bots by the detection technique assisted transfer probability of user activity clickstreams will increase by a mean of 12.8 percent, as per results from our research on real online social network sites, compared to the detection method funded estimate of user behaviour.

Healthcare Professionals' Role in Social Media Public Health Campaigns: Analysis of Spanish Pro Vaccination Campaign on Twitter.

The COVID-19 pandemic has generated a great impact worldwide both on the population health but also on an economic and social level. In this health emergency, a key element has been and still is the need for information, which has become a daily concern for many people. Social media represent powerful tools for searching and gathering health-related information, thus becoming a new place where health authorities need to be present to disseminate information of preventive measures like vaccines against COVID-19, as well as try to block information against these public health measures. The main goal of this study was to analyze the role that healthcare professionals have in Twitter to support the campaign of public institutions on vaccination against COVID-19. To address this study, an analysis of the messages sent on Twitter containing the hashtag #yomevacuno, between 12 December 2020 was developed using the NodeXL software (Social Media Research Foundation, Redwood, CA, USA), focusing on content analysis of tweets and users’ accounts to identify healthcare professionals. The results show that healthcare professionals represent only 11.38% of users, being responsible for 6.35% of impressions generated by the network #yomevacuno. We can observe that traffic information generated by healthcare professionals is not significant in comparison with institutions (p = 0.633), but it is compared to common users (p = 0.0014). The most active healthcare professionals were pharmacists (40.17%), nurses (27.17%), and physicians (12.14%). Their activity (90.43% of messages) was mainly focused on sharing messages generated by other users’ accounts. From original content generated by healthcare professionals, only 78.95% had a favorable storytelling on the vaccine, but without sharing information about vaccines or vaccination. As a conclusion for this study, the participation of healthcare professionals in the dissemination and generation of information within the #yomevacuno communication strategy, led by the Spanish Ministry of Health, has been scarce. We emphasize the need to enhance communication skills in social networks to support public health campaigns through these increasingly important social media.

Analysis of Geotagging Behavior: Do Geotagged Users Represent the Twitter Population?

Twitter’s APIs are now the main data source for social media researchers. A large number of studies have utilized Twitter data for diverse research interests. Twitter users can share their precise real-time location, and Twitter APIs can provide this information as longitude and latitude. These geotagged Twitter data can help to study human activities and movements for different applications. Compared to the mostly small-scale data samples in different domains, such as social science, collecting geotagged data offers large samples. There is a fundamental question whether geotagged users can represent non-geotagged users. While some studies have investigated the question from different perspectives, they did not investigate profile information and the contents of tweets of geotagged and non-geotagged users. This empirical study addresses this limitation by applying text mining, statistical analysis, and machine learning techniques on Twitter data comprising more than 88,000 users and over 170 million tweets. Our findings show that there is a significant difference (p-value < 0.001) between geotagged and non-geotagged users based on 73% of the features obtained from the users’ profiles and tweets. The features can also help to distinguish between geotagged and non-geotagged users with around 80% accuracy. This research illustrates that geotagged users do not represent the Twitter population.

Barriers to Long-Term Maintenance of a Gluten-Free Diet in People With Celiac Disease

ObjectivesCurrently the only treatment for celiac disease (CD), an autoimmune disease triggered by ingestion of the protein gluten, is a gluten-free (GF) diet. This study aimed to examine some barriers (GF food accessibility, social support, GF food knowledge) to maintaining a GF diet. MethodsA deidentified online survey with REDCap was shared with people with celiac disease via social media (celiac disease group and research survey exchange group via Reddit, research survey exchange groups via Facebook, celiac disease Discord server). The survey included questions about diagnosis, symptoms, social support, eating habits, GF food access, disease impact, gluten-free knowledge, and demographics. Analysis included descriptive statistics and qualitative measures were used to determine themes. ResultsOf the 123 responses, 54.5% were diagnosed with CD by small intestine biopsy, 85.1% maintained a GF diet, and 35.2% had CD symptoms for 1–4 years before receiving a diagnosis. Concerning accessibility, 47.9% reported having some difficulty affording GF foods and 49.2% that local grocery stores had limited selection of GF foods. An analysis of GF bread cost in one Washington State county showed a mean cost per loaf of $6.52 which was $4.98 higher than the average cost of all bread in the U.S. When it came to checking food labels for gluten, 59% reported feeling very confident and most participants were able to correctly identify foods that may contain gluten; however, less than half (47.5%) identified kamut (a type of wheat) as a gluten containing grain. 46.7% reported feeling that having CD impacts their life daily. The majority (64.2%) of participants stated that family and friends are supportive of needs, and 62.3% also shared that they did not live in a home that was free of gluten. ConclusionsThe results from this study suggest that there may be several types of barriers to maintaining a GF diet in people with CD. This study aims to bring better awareness of the prevalence of food accessibility, social support, and GF food knowledge barriers to those living with CD, and to the nutrition professionals who provide their healthcare. Funding SourcesBastyr University Faculty Student Research Grant

How to gauge investor behavior? A comparison of online investor sentiment measures

Given the increasing interest in and the growing number of publicly available methods to estimate investor sentiment from social media platforms, researchers and practitioners alike are facing one crucial question – which is best to gauge investor sentiment? We compare the performance of daily investor sentiment measures estimated from Twitter and StockTwits short messages by publicly available dictionary and machine learning based methods for a large sample of stocks. To determine their relevance for financial applications, these investor sentiment measures are compared by their effects on the cross-section of stocks (i) within a Fama and MacBeth (J Polit Econ 81:607–636, 1973) regression framework applied to a measure of retail investors’ order imbalances and (ii) by their ability to forecast abnormal returns in a model-free portfolio sorting exercise. Interestingly, we find that investor sentiment measures based on finance-specific dictionaries do not only have a greater impact on retail investors’ order imbalances than measures based on machine learning approaches, but also perform very well compared to the latter in our asset pricing application.

‘But her age was not given on her Facebook profile’: minors, social media, and sexual assault trials.

ABSTRACT This paper examines the role of social media evidence in sexual assault trials in Canada, focusing on cases with underage female victims. Teenage girls are among the heaviest social media users and face unique expectations regarding the performance of heteronormative gender norms. Society simultaneously encourages girls to enact gender roles that emphasize their femininity and sexuality and punishes them for acting according to these standards. When girls engage in performativity online, they leave behind a digital footprint that can be used against them at trial. Through a detailed case study of 14 publicly available judgments, we analyze how judges evaluate girls’ social media content in sexual assault trials that feature a mistake of age defense. Drawing on social media research, legal studies, and the concept of performativity, we show that judges vary greatly in their understandings of gender norms and that this translates to divergent case outcomes. In the ‘guilty’ cases, the judges contextualize social media content as insufficient and unreliable, noting that it is common for youth to lie or embellish facts online. In the ‘not guilty’ cases however, the judges appear to take such evidence at face value and hold girls accountable for having provocative pictures or misrepresenting themselves online. Such practices are problematic because they perpetuate rape myths and misconceptions about victim behavior. We call for greater consideration of the socio-cultural norms that govern girls’ social media use to avoid biased interpretations that adversely shape the outcome of sexual assault trials.

Challenges and Opportunities in Social Media Research in Gastroenterology.

In recent years, social media has transformed how we as gastroenterologists communicate with each other and has grown into an arena of knowledge and peer support for patients. Gastroenterologists commonly use social media for education networking, patient populations use social media for peer support and advocacy, but little is known about how gastroenterologists can use social media to conduct thoughtful and rigorous patient-centered research. Therefore, we aim to introduce the scope of social media research, highlight prominent examples in gastroenterology, and review innovative opportunities and unique challenges to using and studying social media for research.

Posting Bot Detection on Blockchain-based Social Media Platform using Machine Learning Techniques

Steemit is a blockchain-based social media platform, where authors can get author rewards in the form of cryptocurrencies called STEEM and SBD (Steem Blockchain Dollars) if their posts are upvoted. Interestingly, curators (or voters) can also get rewards by voting others' posts, which is called a curation reward. A reward is proportional to a curator's STEEM stakes. Throughout this process, Steemit hopes "good" content will be automatically discovered by users in a decentralized way, which is known as the Proof-of-Brain (PoB). However, there are many bot accounts programmed to post automatically and get rewards, which discourages real human users from creating good content. We call this type of bot a posting bot. While there are many papers that studied bots on traditional centralized social media platforms such as Facebook and Twitter, we are the first to study posting bots on a blockchain-based social media platform. Compared with the bot detection on the usual social media platforms, the features we created have an advantage that posting bots can be detected without limiting the number or length of posts. We can extract the features of posts by clustering distances between blog data or replies. These features are obtained from the Minimum Average Cluster from Clustering Distance between Frequent words and Articles (MAC-CDFA), which is not used in any of the previous social media research. Based on the enriched features, we enhanced the quality of classification tasks. Comparing the F1-scores, the features we created outperformed the features used for bot detection on Facebook and Twitter.

Investor relations in the era of social media: systematic literature review of social media as a strategic corporate disclosure tool

PurposeThis paper aims to systematically review how corporations are increasingly using social media to strategically disseminate information to investors, including different research tracks, then identify the gaps to propose future research opportunities.Design/methodology/approachThe authors searched for relevant scholarly work on Scopus and Google Scholar databases published during the period 2000–2020 in English. Both quantitative and qualitative papers were reviewed. Articles were filtered based on their relevance to the study's goal, resulting in the selection of 84 articles. A total of 16 articles were selected for inclusion in the systematic review.FindingsIn light of the existing studies’ limitations, this paper derives and summarizes 16 leading future research tracks. Results indicated that corporations could use social media to reduce information asymmetry between managers and investors. Nevertheless, social media for information disclosure purposes is used in a strategic way, whereby only positive news and voluntary information are disseminated.Research limitations/implicationsThe implications for investors are that they can make better decisions by engaging in the process of “the wisdom of crowd,” which is facilitated by reciprocal communication. The implications for corporations are that sharing earning information through social networking platforms presents them with an opportunity to effectively manage their investors by reducing negative perceptions and increasing market response.Originality/valueAs far as we know, this is the first paper that uses a systematic literature review over the social media research field.

The collective storytelling organisational framework for social media use

The organisational implementation and use of social media for online community engagement is plagued with many challenges. The result is managers being frustrated at not achieving their desired results. Despite an increase in social media research, it is evident that some critical aspects of social media use by organisations are left unexplained by existing theories. The purpose of this research study is to investigate how social media is used within organisations to engage with its online community. The grounded theory method (GTM) was used to develop a substantive theory that increases understanding of this phenomenon. Two organisations were selected as the case studies. Both are industry leaders in South Africa, with one being a prominent retailer with a visible social media presence and the other, being a leading university in South Africa, which is actively growing its social media presence. The results show that organisations enter a collective storytelling process with their online community. The need to reduce risk to reputation and improve on the levels of online community engagement are identified as reasons for this. The strategic alignment of the social media function and the organisational social media use characteristics set the backdrop for the collective storytelling process, while content quality influences the richness of this process. Challenges associated with the collective storytelling process lead to the development and refinement of the organisational social media strategy, which in turn helps to reduce risk to reputation and improve online community engagement.

Expression in the Virtual Public: Social Justice Considerations in Harvesting Youth Online Discussions for Research Purposes

Information posted by youth in online social media contexts is regularly accessed, downloaded, integrated, and analyzed by academic researchers. The practice raises significant social justice considerations for researchers including issues of representation and equitable distribution of risks and benefits. Use of this type of data for research purposes helps to ensure representation in research of the voices of (sometimes marginalized) youth who participate in these online contexts, at times discussing issues that are also under-represented. At the same time, youth whose data are harvested are subject (often without notice or consent) to the risks associated with this research, while receiving little if any direct benefit from the work. These risks include the potential loss of online social community as well as threats to participant rights and wellbeing. This paper explores the tension between the social justice benefit of representation and considerations that would suggest caution, the latter including inequitable distribution of research-related costs and benefits, and the traditional ethics concerns of participant autonomy and privacy in the context of youth participation in online discussions. In the final section, we propose guidelines and considerations for the conduct of online social media research to assist researchers to balance and respect representational and participant rights or wellbeing considerations, especially with youth.

DOES CONTENT DISSEMINATION THROUGH FACEBOOK MATTER FOR GOVERNMENT DEPARTMENTS: A STUDY OF KERALA POLICE DEPARTMENTS FACEBOOK PAGE

Government organisationsare generally known to be lagging behind their citizens in the use of social networking sites with half of the departments having little or no presence in such platforms. This study aims at understanding what type of content affects citizens attitude towards a Government Departments social media pages and how they perceive the message disseminated through such platforms. The researchers have selected the case of the Kerala Police Departments (KPD) Facebook page for the present study. Respondents who are post graduate students from various departments of Mahatma Gandhi University, Kerala were subject to different type and formats of content stimuli to assess their attitude towards the content type/format itself and attitude towards the department through a questionnaire. Not only will such a study contribute towards the knowledge base on social media research, this study will also help police department across states in India to develop appropriate content for social media to reach their citizens. In order to test the hypotheses and identify interactions between the dependent and independent variables, one-way ANOVA and independent sample t-tests were used. The results revealed significant differences in attitude towards KPD across stimuli and also attitude towards the stimuli itself. Among the various content type provided as stimuli, Hilarious memes generated the most favourable attitude towards the department. The attitude of the respondents towards post re-posting user content was the most favourable. Image/ photo content generates more positive attitude towards the department compared to video content. The study has also revealed that there is a significant difference between the attitudes of respondents who have had priorinteractionwith the Facebook page of KPDversus those who have had no priorinteraction.

Repurposing Digital Methods in a Post-API Research Environment: Methodological and Ethical Implications

Especially after the social media curtailing brought about the Cambridge Analytica scandal, it has become increasingly difficult to do social media research by using digital methods as well as following the medium . This condition brings in new methodological and ethical challenges. This article proposes some methodological strategies to ‘repurpose’ digital methods in a post-API research environment. The discussion draws on three case studies: 1) studying Instagram stories: the scraping dilemma; 2) studying smartphone in everyday contexts: researching digital environments not connected to APIs; 3) studying fake news on Twitter: dealing with increasingly useless APIs data. For each case study methodological and ethical implications are examined. In conclusion, the article suggests that a possible viable strategy to repurpose digital methods in a post-API era is to follow the natives (along with the medium ), that is, to take advantage of the natively digital methods through which social media users manage their own data as well as emic conception of what is ethical (or at least acceptable) regarding the handling of their own data.

‘I feel the irritation and frustration all over the body’ Affective ambiguities in networked parenting culture

This article investigates the affective power of social media by analysing everyday encounters with parenting content among mothers. Drawing on data composed of diaries of social media use and follow-up interviews with six women, we ask how our study participants make sense of their experiences of parenting content and the affective intensities connected to it. Despite the negativity involved in reading and participating in parenting discussions, the participants find themselves wanting to maintain the very connections that irritate them, or even evoke a sense of failure, as these also yield pleasure, joy and recognition. We suggest that the ambiguities addressed in our research data speak of something broader than the specific experiences of the women in question. We argue that they point to the necessity of focusing on, and working through affective ambiguity in social media research in order to gain fuller understanding the complex appeal of platforms and exchanges.

Students' Attitudes Towards Vocational Education in Albania and the Challenges of the COVID-19 Pandemic

The COVID-19 pandemic has posed serious challenges to the Albanian education system, schools, universities, colleges, childcare, which all had to shut down to stop the spread of the virus. This led to adaptation and an instant introduction of online education while students, teachers and other stakeholders were not prepared for it. The Albanian Vocational Education and Training (VET) schools and institutions were the most affected by the difficulties of the system to adapt to online learning, because the VET students are more in need of practical knowledge and skills development. This article is intended to acquire knowledge about the basic concepts and theories of attitude: nature, definition, and importance, to explore the dimensionality of Albanian students' attitudes towards vocational education through literature review, qualitative research and social media research and the COVID-19 pandemic challenges. Research of theories to understand this concept and definitions of various scholars related to them in this article suggest some recommendations on how to improve the poor image and low reputation that vocational education has suffered in Albania. VET is not always preferred within the Albanian society and is often considered a second opportunity for low success-rate faculty students.

#urbanforest: cultural ecosystem services of urban trees through the lens of Instagram

Purpose The non-material benefits which people derive from ecosystems, cultural ecosystem services (CES), can be difficult to measure and quantify. This study aims to demonstrate the usefulness of social media analysis. Design/methodology/approach The widespread use of social media applications has provided a novel methodology for obtaining crowd-sourced data, which can reveal patterns in how social media users interact with urban greenspace and participate in place-making activities. This study explores how urban trees are represented in images tagged with the city of Bolzano, Italy, and uploaded over the course of a year to the image-sharing application Instagram. Findings A third of all the images contained some elements of green nature, with 3.1% of the images portraying urban trees as the main subject and 11% with urban trees as background features. Seasonal preferences for winter and summer scenes emerged. Accompanying text, in the form of hashtags and image descriptions, was mostly positive and showed how enthusiastically people describe urban nature. An assessment of the images in terms of CES revealed that beyond aesthetic factors and the inspiration to take photographs of nature, a wide range of CES are represented, reflecting the recognition of the benefits of urban trees by Instagrammers. The collection of images provided a unique snapshot of the city of Bolzano. Practical implications This reinforces the importance of urban trees within planning policy for providing sense of place, recreation and stress relief for residents and tourists. Originality/value The study builds on recent advances in social media research, focussing on the important field of urban CES.

Young Adults' Mental Illness Aesthetics on Social Media

Social media posts expressing mental illness such as depression are trending in today's society. The aesthetics of dark and depressing posts are highlighted in blogs or social media accounts of young individuals. Consequently, this study investigated why young people use mental illness as an aesthetic on social media. On top of that, this study contributes to the limited body of research on this subject. This study applied a method known as netnography, an analysis of social interactions online. Furthermore, the actor-network theory (ANT) was employed as an analytical tool to explore insights and draw conclusions. Seven mediators were identified as possible causes that prompted mental illness aesthetic use, including Tumblr, media, attention seekers, coping mechanism, victimhood, emo culture, and mental health awareness. These findings provided insights into developing interventions and systematic methods to discuss mental illness properly. This study also identified current challenges in social media research regarding mental illness detection.