Large Social Media Research Articles

Crowdsourcing Adverse Events Associated With Monoclonal Antibodies Targeting Calcitonin Gene–Related Peptide Signaling for Migraine Prevention: Natural Language Processing Analysis of Social Media

Background Clinical trials demonstrate the efficacy and tolerability of medications targeting calcitonin gene–related peptide (CGRP) signaling for migraine prevention. However, these trials may not accurately reflect the real-world experiences of more diverse and heterogeneous patient populations, who often have higher disease burden and more comorbidities. Therefore, postmarketing safety surveillance is warranted. Regulatory organizations encourage marketing authorization holders to screen digital media for suspected adverse reactions, applying the same requirements as for spontaneous reports. Real-world data from social media platforms constitute a potential venue to capture diverse patient experiences and help detect treatment-related adverse events. However, while social media holds promise for this purpose, its use in pharmacovigilance is still in its early stages. Computational linguistics, which involves the automatic manipulation and quantitative analysis of oral or written language, offers a potential method for exploring this content. Objective This study aims to characterize adverse events related to monoclonal antibodies targeting CGRP signaling on Reddit, a large online social media forum, by using computational linguistics. Methods We examined differences in word frequencies from medication-related posts on the Reddit subforum r/Migraine over a 10-year period (2010-2020) using computational linguistics. The study had 2 phases: a validation phase and an application phase. In the validation phase, we compared posts about propranolol and topiramate, as well as posts about each medication against randomly selected posts, to identify known and expected adverse events. In the application phase, we analyzed posts discussing 2 monoclonal antibodies targeting CGRP signaling—erenumab and fremanezumab—to identify potential adverse events for these medications. Results From 22,467 Reddit r/Migraine posts, we extracted 402 (2%) propranolol posts, 1423 (6.33%) topiramate posts, 468 (2.08%) erenumab posts, and 73 (0.32%) fremanezumab posts. Comparing topiramate against propranolol identified several expected adverse events, for example, “appetite,” “weight,” “taste,” “foggy,” “forgetful,” and “dizziness.” Comparing erenumab against a random selection of terms identified “constipation” as a recurring keyword. Comparing erenumab against fremanezumab identified “constipation,” “depression,” “vomiting,” and “muscle” as keywords. No adverse events were identified for fremanezumab. Conclusions The validation phase of our study accurately identified common adverse events for oral migraine preventive medications. For example, typical adverse events such as “appetite” and “dizziness” were mentioned in posts about topiramate. When we applied this methodology to monoclonal antibodies targeting CGRP or its receptor—fremanezumab and erenumab, respectively—we found no definite adverse events for fremanezumab. However, notable flagged words for erenumab included “constipation,” “depression,” and “vomiting.” In conclusion, computational linguistics applied to social media may help identify potential adverse events for novel therapeutics. While social media data show promise for pharmacovigilance, further work is needed to improve its reliability and usability.

Uncovering coordinated cross-platform information operations: Threatening the integrity of the 2024 U.S. presidential election

Information operations (IOs) pose a significant threat to the integrity of democratic processes, with the potential to influence election-related online discourse. In anticipation of the 2024 U.S. presidential election, we present a study aimed at uncovering the digital traces of coordinated IOs on X (formerly Twitter). Using our machine learning framework for detecting online coordination, we analyze a dataset comprising election-related conversations on X from May to July 2024. This reveals a network of coordinated inauthentic actors, displaying notable similarities in their link-sharing behaviors. Our analysis shows concerted efforts by these accounts to disseminate misleading, redundant, and biased information across the Web through a coordinated cross-platform information operation: The links shared by this network frequently direct users to other social media platforms or mock news sites featuring low-quality political content and, in turn, promoting the same X and YouTube accounts. Members of this network also shared deceptive images generated by AI, accompanied by language attacking political figures and symbolic imagery intended to convey power and dominance. While X has suspended or restricted a subset of these accounts, 75 percent ofthe coordinated network remains active, garnering substantial traction over time: The suspicious Web sites promoted by this coordinated network are shared thousands of times per day by the X user base, further amplifying their reach and potential impact. Our findings underscore the critical role of developing computational models to scale up the detection of threats on large social media platforms, and emphasize the broader implications of these techniques to detect IOs across the wider Web.

Best practices for studies using digital data donation

AbstractDigital trace data form a rich, growing source of data for social sciences and humanities. Data donation offers an innovative and ethical approach to collect these digital trace data. In data donation studies, participants request a copy of the digital trace data a data controller (e.g., large digital social media or video platforms) collected about them. The European Union’s General Data Protection Regulation obliges platforms to provide such a copy. Next, the participant can choose to share (part of) this data copy with the researcher. This way, the researcher can obtain the digital trace data of interest with active consent of the participant. Setting up a data donation study involves several steps and considerations. If executed poorly, these steps might threaten a study’s quality. In this paper, we introduce a workflow for setting up a robust data donation study. This workflow is based on error sources identified in the Total Error Framework for data donation by Boeschoten et al. (2022a) as well as on experiences in earlier data donation studies by the authors. The workflow is discussed in detail and linked to challenges and considerations for each step. We aim to provide a starting point with guidelines for researchers seeking to set up and conduct a data donation study.

Balancing benefits and risks of exercise in pregnancy: a qualitative analysis of social media discussion

Exercise improves pregnancy outcomes, but few pregnant individuals meet physical activity guidelines. The main objective of this study was to explore the perception of exercise during pregnancy using posts and...

Measurement of the Public Activity Richness of Urban Park Based on Large Language Models and Social Media Data: A Case Study of Shanghai

Measurement of the Public Activity Richness of Urban Park Based on Large Language Models and Social Media Data: A Case Study of Shanghai

People believe political opponents accept blatant moral wrongs, fueling partisan divides.

Efforts to bridge political divides often focus on navigating complex and divisive issues, but eight studies reveal that we should also focus on a more basic misperception: that political opponents are willing to accept basic moral wrongs. In the United States, Democrats, and Republicans overestimate the number of political outgroup members who approve of blatant immorality (e.g. child pornography, embezzlement). This "basic morality bias" is tied to political dehumanization and is revealed by multiple methods, including natural language analyses from a large social media corpus and a survey with a representative sample of Americans. Importantly, the basic morality bias can be corrected with a brief, scalable intervention. Providing information that just one political opponent condemns blatant wrongs increases willingness to work with political opponents and substantially decreases political dehumanization.

Social media sensors as early signals of influenza outbreaks at scale

Detecting early signals of an outbreak in a viral process is challenging due to its exponential nature, yet crucial given the benefits to public health it can provide. If available, the network structure where infection happens can provide rich information about the very early stages of viral outbreaks. For example, more central nodes have been used as social network sensors in biological or informational diffusion processes to detect early contagious outbreaks. We aim to combine both approaches to detect early signals of a biological viral process (influenza-like illness, ILI), using its informational epidemic coverage in public social media. We use a large social media dataset covering three years in a country. We demonstrate that it is possible to use highly central users on social media, more precisely high out-degree users from Twitter, as sensors to detect the early signals of ILI outbreaks in the physical world without monitoring the whole population. We also investigate other behavioral and content features that distinguish those early sensors in social media beyond centrality. While high centrality on Twitter is the most distinctive feature of sensors, they are more likely to talk about local news, language, politics, or government than the rest of the users. Our new approach could detect a better and smaller set of social sensors for epidemic outbreaks and is more operationally efficient and privacy respectful than previous ones, not requiring the collection of vast amounts of data.

Investigating Health and Well-Being Challenges Faced by an Aging Workforce in the Construction and Nursing Industries: Computational Linguistic Analysis of Twitter Data.

Construction and nursing are critical industries. Although both careers involve physically and mentally demanding work, the risks to workers during the COVID-19 pandemic are not well understood. Nurses (both younger and older) are more likely to experience the ill effects of burnout and stress than construction workers, likely due to accelerated work demands and increased pressure on nurses during the COVID-19 pandemic. In this study, we analyzed a large social media data set using advanced natural language processing techniques to explore indicators of the mental status of workers across both industries before and during the COVID-19 pandemic. This social media analysis aims to fill a knowledge gap by comparing the tweets of younger and older construction workers and nurses to obtain insights into any potential risks to their mental health due to work health and safety issues. We analyzed 1,505,638 tweets published on Twitter (subsequently rebranded as X) by younger and older (aged <45 vs >45 years) construction workers and nurses. The study period spanned 54 months, from January 2018 to June 2022, which equates to approximately 27 months before and 27 months after the World Health Organization declared COVID-19 a global pandemic on March 11, 2020. The tweets were analyzed using big data analytics and computational linguistic analyses. Text analyses revealed that nurses made greater use of hashtags and keywords (both monograms and bigrams) associated with burnout, health issues, and mental health compared to construction workers. The COVID-19 pandemic had a pronounced effect on nurses' tweets, and this was especially noticeable in younger nurses. Tweets about health and well-being contained more first-person singular pronouns and affect words, and health-related tweets contained more affect words. Sentiment analyses revealed that, overall, nurses had a higher proportion of positive sentiment in their tweets than construction workers. However, this changed markedly during the COVID-19 pandemic. Since early 2020, sentiment switched, and negative sentiment dominated the tweets of nurses. No such crossover was observed in the tweets of construction workers. The social media analysis revealed that younger nurses had language use patterns consistent with someone experiencing the ill effects of burnout and stress. Older construction workers had more negative sentiments than younger workers, who were more focused on communicating about social and recreational activities rather than work matters. More broadly, these findings demonstrate the utility of large data sets enabled by social media to understand the well-being of target populations, especially during times of rapid societal change.

Is it about “them”? leveraging big data research to understand anti-immigrant discourse

The paper explores the potential of big data analytics for researching anti-immigrant discourse. We emphasize contextualization as an essential element of research and follow a hybrid approach inspired by best practices of computational content analysis, combining human hermeneutic expertise with supervised machine learning to classify a corpus of comments in online news communities in Singapore over 6 months ( N = 399,225). The paper highlights how big data analytics can provide a nuanced and critical apprehension of immigrant-related discourse in large social media datasets.

OWNED MEDIA: SYSTEMATIC LITERATURE REVIEW (SLR)

E-marketing communications offer a great way to establish and enhance connections with customers. In this digital realm, there are various key strategies to consider. One of them is delivering relevant and captivating content that truly resonates with the target audience. Another strategy involves encouraging internet users to engage with the content by leaving comments, sharing their own content, or even participating in interactive games provided by the company. The main objective of this study is to gain a deeper understanding of the knowledge, characteristics, and impact of owned media on digital marketing. To conduct this research, the Preferred Reporting Items for Systematic Review and Meta Analysis related to owned media were utilized. Data was collected from multiple journal sites indexed in Scopus over a span of six years. The findings of this study reveal that having a large social media following does not necessarily translate to increased sales. In fact, owned social media platforms tend to be more effective for brands with a smaller number of followers. Additionally, while it may be tempting to adopt a one-size-fits-all global social media strategy, it is crucial to take into account the cultural context of each country. In countries with a high power distance, a more nuanced approach is required for owned social media to be truly effective. This research contributes to a better understanding of the functions of social media and provides valuable insights for developing effective marketing strategies.

Adaptive link dynamics drive online hate networks and their mainstream influence

Online hate is dynamic, adaptive— and may soon surge with new AI/GPT tools. Establishing how hate operates at scale is key to overcoming it. We provide insights that challenge existing policies. Rather than large social media platforms being the key drivers, waves of adaptive links across smaller platforms connect the hate user base over time, fortifying hate networks, bypassing mitigations, and extending their direct influence into the massive neighboring mainstream. Data indicates that hundreds of thousands of people globally, including children, have been exposed. We present governing equations derived from first principles and a tipping-point condition predicting future surges in content transmission. Using the U.S. Capitol attack and a 2023 mass shooting as case studies, our findings offer actionable insights and quantitative predictions down to the hourly scale. The efficacy of proposed mitigations can now be predicted using these equations.

Consumer and brand value formation, value creation and co-creation in social media brand communities

PurposeSocial media has significantly impacted the value creation processes within the consumer–brand relationship. This study aims to examine value formation processes within a cosmetics social media brand community and to establish the types of value formation associated with different categories of interactions within a social media brand community.Design/methodology/approachThe research adopted a netnographic approach and followed the operational protocols of netnography. Conversations in one large cosmetics social media brand community were observed and downloaded for analysis over a two-month period. Examples of value-creation and formation processes were identified using netnographic interpretative procedures to develop higher-order themes.FindingsThe findings supported the creation of a “Consumer and brand value creation and co-creation framework” highlighting disparate value types within the following interactions: consumer-to-consumer; brand-to-consumer; and consumer-to-brand. The identified value types were specific to the actors (i.e. consumers and brands) involved in value formation processes. The analysis also revealed consumers’ ability to independently generate value through direct interaction with a social media brand community and the brands’ role in supporting consumers in value formation through value facilitation.Originality/valueThe pivotal role of disparate actors’ interactions in value formation processes is highlighted, alongside the autonomous ability to form value with the aid of resources stored and shared within the social media brand community. The network of interactions and value-creation processes contribute to a holistic understanding of the interactions in a social media brand community. Furthermore, the research explores and highlights the emerging role of social media brand communities as “value vestiges”.

The Contributing Factors of High Consumer Loyalty to Jellycat Brand

E-commerce platforms and social media have made brand-consumer connections easier in China. Jellycat has gained social media traffic due to its innovative product design. Jellycat brand products usually attract youthful consumers, who buy them consistently and build brand loyalty. This study examined Jellycat's brand loyalty factors. Consumer behavior, psychology, and marketing theories were used to draw conclusions from Jellycat's purchase data. Factor one: Jellycat's product design, which uses personification and inspiration from everyday objects to make toys, refreshes and gains customers. The essay advises the corporation to closely regulate product quality to attract long-term customers. Second, an emotional bond Jellycat's anthropomorphic toys help consumers who feel stressed and lonely during societal growth form profound emotional bonds. The article advises that the brand formally establish social media discussion groups to strengthen the emotional tie, increase brand-customer interactions, and boost loyalty. Brand recall comes in third. Due to its high traffic and visibility, the brand has a large social media following and is ready to buy. The report suggests Jellycat use social media influencers to boost brand awareness and loyalty.

Designing an information system for integrated topic analysis of social media big data

Open communities of users in social media are a source of data that quickly presents the thematic agenda of issues relevant to the population. The indicators of user activity are views, likes, comments and reposts, and they are of a dynamic nature. The article presents a new vision at the topic modeling problems, the results of which are examined for dynamic properties. These data are relevant to solve problems of information support for regional and municipal development. The authors reveal their experience in designing an information system for integrated topic analysis of large open social media data. The system is based on three technologies: building dynamic topic models for monitoring social media, intelligent analysis of topic modeling results; and cognitive visualization of dynamic topic modeling results. To take into account design uncertainty, object modeling tools, system design and a modular approach were used.

(236) Evaluating the Social Media Landscape Surrounding Men’s Health Conditions in Testicular Cancer Patients

Abstract Introduction Forms of sexual dysfunction remain some of the most common concerns amongst testicular cancer survivors. While it is commonly reported, discussions surrounding male sexual dysfunction among patients with testicular cancer in public social media forums are understudied. Objective We sought to evaluate themes and tones on Reddit, a large social media platform, regarding men’s health conditions in patients with testicular cancer. Methods We retrospectively analyzed discussion posts on Reddit using qualitative analysis and natural language processing-based sentiment analysis. Using the Reddit application programming interface (API), 1000 posts from April to June 2023 were extracted from the subreddit r/testicularcancer, which is dedicated to discussions related to testicular cancer and has &amp;gt;5,900 active members. Men’s health issues were defined to include erectile dysfunction, low libido, testicular discomfort, or ejaculatory dysfunction (e.g., delayed or premature ejaculation, anejaculation, painful ejaculation). Qualitative analysis was performed to determine overall themes within discussion posts. Sentiment analysis was performed using the validated tool VADER, which is specifically attuned to sentiments expressed on social media platforms and assigns a score for each post that can be interpreted as having a positive (score of 1), neutral (score of 0), or negative (score of -1) sentiment. Results A total of 148 posts were randomly selected for thematic and sentiment analysis. Notable discussion themes from the posts include discussing treatment options (e.g., chemotherapy vs. surgery vs. observation) offered by the physician (24.3%); asking about side effects of treatment (17.6%); discussing a patient’s personal journey with testicular cancer (33.1%); asking for advice from the online community (68.9%); and discussing various emotions (frustration, anxiety, stress, etc.) (28.4%). Fifteen (10.1%) posts mentioned a men’s health issue within the text body. Of these 15 posts, 7 discussed low libido, 4 discussed testicular pain or discomfort, 3 highlighted ejaculatory dysfunction, and 1 highlighted a physiologic effect of low testosterone levels. The mean (SD) VADER score was 0.1 (0.9); most posts (75; 51.0%) had a positive sentiment while 62 (42.2%) had a negative sentiment. Posts discussing men’s health issues did not have a significantly stronger positive or negative tone than other posts (p = 0.83). Conclusions On Reddit, the slim majority of posts had positive sentiment and patients seemed to prioritize discussing their journey with testicular cancer and its various treatment options along with asking for community advice and second opinions. Upon initial analysis, a smaller but notable percentage of posts mentioned a men’s health issue, indicating that men’s health issues may be underdiscussed on social media venues despite its prevalence in this particularly vulnerable patient population. A variety of reasons may explain this, including stigma involving discussing sexual dysfunction in public forums and a lack of prioritization and focus on men’s health issues in the context of living with cancer. Disclosure No.

(263) Evaluating Changes in Social Media Discussions Regarding Vasectomies Before and After The Dobbs V. Jackson Supreme Court Decision

Abstract Introduction In June 2022, the U.S. Supreme Court overruled Roe v. Wade, the 1973 case establishing a federally protected right to abortion, through the case Dobbs v. Jackson. Subsequent research has demonstrated an increase in the number of men seeking vasectomy consultations as men take more ownership of family planning. We hypothesized that there might be a similar, paralleled change in online discussions about vasectomy following the court’s decision. Objective We sought to characterize themes and tones in social media discussions regarding vasectomies before and after the Dobbs decision. Methods We analyzed vasectomy-related discussions on Reddit, a large social media platform, using qualitative analysis and natural language processing-based sentiment analysis. Using the Reddit API, 1000 posts from 1 year before Dobbs and 1 year after were extracted from the subreddit group r/vasectomy. The group has 13,400 active members. Qualitative analysis was performed to determine overall themes within discussion posts. Poster age and comments about male sexual dysfunction were noted. Sentiment analysis was performed using the validated software VADER, which is specifically tuned expressions on social media platforms and assigns posts scores that can be interpreted as having positive, neutral, or negative sentiments. Results 213 total posts (107 pre-Dobbs and 106 post-Dobbs) were randomly selected for thematic and sentiment analysis. Posters in the post-Dobbs period were significantly younger than posters in the pre-Dobbs period (25.5 years vs. 31.7 years, p = 0.05). Posters in the post-Dobbs period were also more likely to mention their sexual dysfunction or raise questions regarding their sexual function post-operatively (p = 0.03). Notable discussion themes pre-Dobbs focused on post-operative concerns (n = 31), actionable advice (n = 38), or second opinions (n = 50). Patients also sought to reflect upon their experiences with their vasectomy (n = 30). While similar themes were noted post-Dobbs, more posts focused on describing pre-operative anxieties (n = 36), raising second thoughts regarding a scheduled vasectomy (n = 36), and acknowledging in some way the importance or value of having an online community such as r/vasectomy (n = 60). There was no significant difference in the length of posts (p = 0.44) or the number of positive, neutral, or negative sentiment posts (p = 0.98) between time periods. Conclusions Online discussion forums may provide insight into patients’ experiences with vasectomies during a contentious sociopolitical time when contraceptive options are changing. After the Dobbs decision, patients seemed to express increased pre-operative anxiety and doubt regarding their decisions to get vasectomies, but also expressed greater appreciation for the online community in r/vasectomy. This overall mix of feelings may explain any lack of difference in positive and negative sentiment in posts between the time periods. Disclosure No.

A Novel Architecture for Community Detection Between Large Social Media Creators

This study explores the intricate web of audience overlap among streamers on live streaming platforms. The extensive growth of streaming services has led to a proliferation of individual streamers. A comprehensive understanding of the audience overlap network between these streamers offers valuable insights into user behavior and preferences, presenting unique opportunities for collaboration. This research introduces a novel methodology, leveraging network analysis techniques, to map out the overlap network among individual streamers. The methodology applies advanced principles of overlap detection and community identification within social networks, resulting in an effective approach for discerning overlapping viewer communities. This study has significant implications for enhancing user engagement and collaboration among streamers, as well as improving the effectiveness of recommendations, benefiting streaming platforms, advertisers, and content creators alike

DIGITAL INFRASTRUCTURES AND ENVIRONMENTAL JUSTICE: POLICIES, PRACTICES, AND VISIONS

Environmental media scholars have long drawn attention to the physicality of digital systems, situating their work as part of the infrastructural turn (Larkin, 2013; Parks &amp; Starosielski, 2015; Star, 1999). Contrary to the prevailing “cultural imagination of dematerialization” (Starosielski, 2015), digital supply chains – from data centers to AI systems to consumer electronics – depend on minerals, water, land, labour, and energy (Crawford, 2021; Cubitt, 2016; Hogan et al., 2022). This growth-based model of digital technology is based on assumed access to resources, implicating it in the extractive global economy shaped by ongoing colonial violence (Liboiron, 2021; Spice, 2018). Transdisciplinary scholarship on the intersection of digital technologies and the environment has looked at online organizing and digital climate change action (McLean &amp; Fuller, 2016; Pearce et al., 2019), indigenous resistance and data sovereignty (Duarte, 2017; Kukutai &amp; Taylor, 2016), the environmental impacts of large-scale data centers (Hogan, 2015; Velkova, 2016) and alternative social media (Laser et al., 2022), and what "responsible digitalization" could look like (Dwivedi et al., 2022). Building on already existing work that critically examines the material implications of digital infrastructures, this panel asks what environmental justice means in relation to digital technologies. Turning against the language of revolution that too often gets leveraged by Big Tech to describe the latest "disruptive" technology that is allegedly going to solve the world's problems (Geiger, 2020; Tabel, 2022), we foreground subversive practices, regulatory interventions, and grassroots organizing and vision building as emancipatory alternatives to a for-profit, monopolized internet. From a theory of change that seeks to understand and challenge the extractive nature of digital technology production from all angles, we shed light on reform, repair, refusal, and resistance as paths for transformation. Zooming in on Southeast Louisiana where hundreds of petrochemical processing and manufacturing facilities are located, the first paper examines how Internet access can be reimagined in landscapes shaped by extractive economies. The paper analyzes the challenges that activist and research groups face when using Internet of things (IoT) devices for real-time environmental sensing of air quality due to underdeveloped Internet infrastructures in a region that is becoming increasingly vulnerable to climate change. The second paper engages with the material footprint and environmental implications of computing hardware production. It looks at the "Right to Repair" as one approach that challenges corporate control over design and obsolescence of electronic devices. By comparing examples of recent legislation in the EU, India, and the US, and analyzing them through the lens of design justice and discard studies frameworks, it argues that Right to Repair needs to be complemented by a substantial change in industry norms and practices rather than simply attempting to delay the disposal through repair by consumers. The third paper examines community resistance to data centers in the United States. In the past years, activists have framed their resistance to data centers along three critiques, namely noise pollution, resource consumption, and lack of public input to permitting processes. The paper investigates how environmental justice activists use formal legal and regulatory processes such as public meetings, petitions, lawsuits, public records requests to organise against new data center developments, and the challenges they meet as part of their organising. The fourth paper presents a "feminist principle of the internet on the environment" that was developed over several years in transnational collaborative work by practitioners. It addresses the interconnections between gendered online violence against land and environmental defenders on large social media platforms and on-the-ground resistance to extractive industries and outlines a new emancipatory vision for a different internet that centers planetary care and justice for communities and ecosystems. The fifth paper presents an analysis of the Internet Architecture Board's (IAB) workshop on "Environmental Impact of Internet Applications and Systems", held online in December 2022. It uses an infrastructural lens to analyze which politics are embedded and missing from industry responses to the sector's environmental harms. While international regulatory bodies are slowly coming to terms with the environmental impacts of distributed digital networks, the paper argues that the proposed sustainability solutions are as of yet too narrow in scope.

How Ephemerality Features Affect User Engagement with Social Media Platforms

User engagement, a key factor in the success of social media platforms, has long been based on permanent content. A recent paradigm shift in platform design has led large social media providers to implement ephemerality features that by default make shared content disappear after a certain amount of time. However, very little is known about how ephemerality features affect user engagement and behavior in social media. Drawing upon the technology affordance perspective, we conducted a qualitative multimethod study involving individual interviews and focus groups. Our findings show that the affordances arising from features with varying degrees of ephemerality (i.e., snaps and stories) differ from those of permanent content features in terms of self-presentation, browsing others’ content, and communication. Adopting a multidimensional conceptualization of user engagement, we show the positive (e.g., more content sharing) and negative (e.g., cognitive burden from context loss) effects for snaps and stories that should be cautiously considered by social media platforms aiming to introduce such features. Finally, we reveal new user behaviors that relate to sharing snapshots of fleeting value as snaps or experiences of transient value as stories.

ABOARD Cohort; a national initiative to involve citizens in AD research

AbstractBackgroundMany research cohorts consist of selected research populations, and their outcomes may not translate directly to daily life. Patient Reported Outcomes (PROs) provide this information, but data across the entire disease trajectory, from ‘at risk’ to dementia, are lacking. To address this gap, paving the way for value‐based health care, we have set up a Dutch national data collection infrastructure. This initiative called the ABOARD Cohort aims to (i) study the AD disease trajectory using both PROs and medical data, (ii) link to available registry data, and (iii) serve as central platform to initiate additional studies.MethodThe ABOARD Cohort (www.aboard‐cohort.nl) is part of the ABOARD project, a national public‐private partnership with &gt;30 partners. The cohort is an ongoing, participant‐centered data‐collection, focused on PROs, a minimal CRF with relevant medical data, and linkage to existing data sources. Eligible participants with or at‐risk of AD and their care‐partners are recruited directly‐to‐participant, via (social) media and leaflets. Informed consent and annual collection of PROs through questionnaires are facilitated online, on separate platforms. Governance is based on the principle of data‐portability, the participant being owner of their own data. Participants optionally consent for their study data to be linked to e.g. health insurance and medical record data. We ensure active public‐involvement through a dedicated participant panel.ResultIn September 2022, the ABOARD Cohort was launched. In the first 4 months, n = 82participants (mean age 56±16, female 53(65%)) signed up via the study portal. 60(73%) gave consent to link their data to registries. The ABOARD Cohort Panel, consisting of 57 participants recruited via social media, provided input on the (consent) procedure, via surveys and panel discussions. The early phase experiences are now used to optimize procedures prior to a large social media campaign inviting participants in Spring 2023. The narrative of this campaign is that participants can contribute an hour of their time to help Alzheimer’s research (Figure).ConclusionThe ABOARD Cohort lays the foundation for a future with personalized medicine for AD. With this large scale societal initiative, we attempt to involve a large number of Dutch citizens in Alzheimer’s research.