Innovating opioid research with social media data: A social network analysis of Twitter conversations

This chapter examines the structure and sentiment of the Twitter response to Nathan Broad's naming as the originator of an image-based sexual abuse incident following the 2017 Australian Football League Grand Final. Employing Social Network Analysis to visualize the hierarchy of Twitter users responding to the incident and Applied Thematic Analysis to trace the diffusion of differing streams of sentiment within this hierarchy, we produced a representation of participatory social media engagement in the context of image-based sexual abuse. Following two streams of findings, a model of social media user engagement was established that hierarchized the interplay between institutional and personal Twitter users. In this model, it was observed that the Broad incident generated sympathetic and compassionate discourses among an articulated network of social media users. This sentiment gradually diffused to institutional Twitter users – or Reference accounts – through the process of intermedia agenda-setting, whereby the narrative of terrestrial media accounts was altered by personal Twitter users over time. Keywords Image-based sexual abuse Informal justice Social network analysis Technology facilitated violence Twitter Digital criminology Citation Broadbent, E. and Thompson, C. (2021), "Justice on the Digitized Field: Analyzing Online Responses to Technology-Facilitated Informal Justice through Social Network Analysis", Bailey, J., Flynn, A. and Henry, N. (Ed.) The Emerald International Handbook of Technology-Facilitated Violence and Abuse (Emerald Studies In Digital Crime, Technology and Social Harms), Emerald Publishing Limited, Bingley, pp. 689-709. https://doi.org/10.1108/978-1-83982-848-520211051 Publisher: Emerald Publishing Limited Copyright © 2021 Ella Broadbent and Chrissy Thompson. Published by Emerald Publishing Limited. This chapter is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of these chapters (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode. License This chapter is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of these chapters (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode. Introduction On the evening of September 30, 2017, the final siren sounded on the Australian Football League (AFL) season, and the Richmond Football Club (RFC) secured their first Premiership cup in 37 years. In the hours following the evening's celebrations, an image of a young woman with a premiership medal around her neck – her face cropped and breasts exposed – began to circulate through social networking platforms and fan forums. This image was quick to disperse through social media channels, becoming a symbol for the victory celebrations of the young men within the team and their army of supporters. It later emerged that the woman photographed had not consented to having the image shared. In the month after this incident, a formal police inquiry was conducted at the request of the victim to protect her anonymity, leading to a gradual reduction of the image's appearance within social and terrestrial media. Following the closure of this investigation, the victim's lawyers issued a statement maintaining that while the image had been taken with her consent, she was under the impression that it had been deleted shortly after – and certainly not distributed via social media (Maurice Blackburn Lawyers, 2017). She sought to drop the charges police laid against the accused both to protect her identity and to prevent further distress (SBS, 2017). On 29 October 2017 – almost a month after the image's release – premiership player Nathan Broad was identified as the person responsible for taking and distributing the original image. A press conference was held with Broad and the president of the RFC, Peggy O'Neal, where Broad issued a statement claiming he would take full responsibility for his actions and confirmed he took and distributed the image without consent (Cherny, 2017). The only formal sanction Broad received from the RFC was a three-week suspension at the beginning of the 2018 AFL season (Cherny, 2017). This incident (henceforth referred to as the “Broad incident”) 1 represents a high-profile case of a certain form of technology-facilitated violence (TFV) – image-based sexual abuse (IBSA). Due to police intervention, attempts were made to remove the original image from circulation on social media. While this image can still be located today, its circulation decreased significantly after police attempted to remove it. As a result of these efforts, the ability to analyze the diffusion of the original incident of nonconsensual sexual imagery was limited. However, the subsequent identification in late October 2017 of Nathan Broad as the individual who took the image generated significant social media interest, and produced a body of historical Twitter data that provided a valuable substrate for us to analyze how social media users sought to contest or condone Nathan Broad's naming and sanction. Incidents such as these hold value for criminological analysis, as they can provide a window into public sentiments on the perpetration of, and institutional responses to, IBSA. Moreover, as criminologists such as Powell, Overington, and Hamilton (2018) have demonstrated, examining responses to high-profile crimes on social media can provide a valuable means of researching the content and diffusion of narratives about crime in the contemporary mediascape. In undertaking such projects, a Social Network Analysis (SNA) methodology provides important insights into the degree of homophily within networks who respond to crimes on social media, and the role of central “nodes” in diffusing narratives about crime and perpetration. 2 Such insights are important given that early work within digital criminology has emphasized the “networked” morphology of contemporary harms – speaking, for example, of “networked misogyny” (Banet-Weiser & Miltner, 2016; Thompson & Wood, 2018, p. 12) – but has yet to examine the structural properties of these networks. To date, criminologists have yet to explore the utility of an SNA approach for examining social media–based responses to IBSA and other criminalized acts. To demonstrate the utility of SNA within this context, this study examined this incident of IBSA in Australia. In addition to answering the questions below, this project was concerned with not only the what of the research process but also the how. Readers are encouraged to consider the results and analysis as they would a pilot study – wherein qualitative Twitter data and a network of user relations were operationalized to generate an initial framework for understanding how structural analysis of incidents of IBSA can better demarcate the spread of sentiment through a network. In examining the Broad incident using this methodology, we sought to address the following questions: What are the structural and intermedia features of Twitter users' responses to IBSA? In what ways do Twitter users contest and/or condone IBSA? These questions enabled us to explore user engagement as a process involving both personal and media accounts, and the interactions they share to contest and/or condone a narrative on an incident of IBSA. Furthermore, our analysis offers a novel approach to analyzing public sentiment toward an incident of IBSA, providing structural and intermedia analysis of the response to the incident. This chapter is divided into four main sections. In section one, we review the relevant literature relating to online engagement, digital platforms, and IBSA. In the next section, we discuss the methodological contributions of this work and reflect on the utility of the methods used in this research for future studies into TFV and IBSA. In section three, we detail the major findings from this research; drawing on an Applied Thematic Analysis (ATA) we outline the narrative promulgated by both journalist and news media accounts, alongside personal Twitter users, and how interactions between these users generated a reverse-flow of sentiment. This is represented within a hierarchized visual framework characteristic of SNA to outline the flow of information and sentiment between different types of users responding to the Broad incident. This process enabled us to identify three “user roles” – Reference, Mediator, and Listener – with each performing distinct functions in the diffusion and reception of sentiment within the network. These user roles demonstrate how responses to crime on social media may be structured by clear hierarchies, with some users occupying dialogically significant positions within these networks. Through an ATA of the tweets responding to Broad's naming in the media, we identified an informal justice-seeking response by users to Broad and his actions, alongside a replication of this sentiment within Reference users over time. The counterhegemonic discourses that appeared in response to Broad disrupted the neutral narrative of the Broad incident within Reference accounts and produced a more favorable and balanced consideration of the harms to the victim. Finally, we conclude by reflecting on the implications of this research for online responses to IBSA. We posit that demarcating the connections between social media actors – Mediators, Listeners, and Reference accounts – may enhance our understanding of their specific role in contesting and altering passive narratives of sexual harm online. Literature Review This chapter is situated amid a burgeoning literature on the spectatorship of, and engagement with, TFV and IBSA (Henry, McGlynn, Flynn, Johnson, Powell, & Scott, 2020; Henry & Powell, 2018). It is important to note that such spectatorship involves not only individual observation of an incident of IBSA but also their response to this observation. Here, the act of spectatorship is not confined simply to the object and viewer, or “the spectator and the spectacle,” but also involves “the association between spectators,” or in this instance structural relations between Twitter users (Wood, 2017, p. 9). This grounds our methodology, in seeking to demarcate the connections that shape engagement on social media platforms, a process which is mediated not only by social forces but also the technological (infra)structure of social networking platforms. Twitter has been described as a “personal public” (Schmidt, 2014, p. 4) – a communicative space framed by the dimensions of software, relations, and rules. The concept of personal publics is not limited to Twitter and operates as a foundation for understanding the mechanics of Web 2.0 and user-generated content and interactions. Within a personal public, information is selected and displayed according to personal relevance criteria such as the social network a user situates themselves within. This is then mediated through ties made explicit by the platform – such as following, retweeting, and liking. Twitter itself can be distinguished from other social networks by the specific articulation of these user relations which are utilized to structure communicative flow – “the nexus of social ties and textual references, based on code-enabled connections” (Schmidt, 2014, p. 6). The foundational concept guiding these Twitter relations is that of “following” users – a unilateral relationship used to subscribe to other users' tweets and calculate user visibility metrics. Replies, retweets, and mentions, function as communicative references that allow for navigation to user profiles. These factors produce a stable and dynamic social networking service consisting of networked and distributed conversations (Schmidt, 2014), which enables potentially exponential public distribution and engagement with nonconsensual sexual imagery such as the image released by Broad. Researchers have noted that social media platforms such as Twitter have allowed for a redemocratization of the public sphere (Papacharissi, 2002). The assembly of counterpublics (Fraser, 1990) by girls and women on social media to contest social exclusion and subordination has been documented within criminological literature (Khoja-Moolji, 2015). Technology has, for example, allowed victims and their supporters to engage in “name and shame” tactics to ensure that behavior of abusers is not excused, and to contest the inadequacy of institutional responses to sexual violence such as TFV (Powell, 2015; Salter, 2013; Wood, Rose, & Thompson, 2019, p. 3). Considering the inadequacy of existing institutional responses to rape and violence against women in the form of state-sanctioned justice (Powell, 2015), social media–enabled informal justice-seeking plays an important role in the way victims of sexual violence and their supporters can create counterhegemonic discourses online. Informal justice and contemporary digital activism movements have been conceptualized as an asymmetrical and nonhierarchical endeavor within Powell, Stratton, and Cameron's (2018) theory of rhizomatic justice. Drawing on Deleuze and Guattari's (1988) figuration of the rhizome, Powell, Stratton et al.’s (2018) theory accounts for the diversity of activist behaviors in a digital context, where organizations, groups, and individuals are linked loosely and embody significant diversity (Funke, 2014). The resulting spread of motivations and agendas can lead these forms of activism to both enhance democracy and new forms of bigotry, which may outweigh the original infraction (Powell, Stratton et al., 2018). This is a constructive explanation for the consequences of informal justice-seeking. The utilization of a rhizomatic analogy, however, implies a flattening of hierarchies within these communities, which minimizes the “algorithmically-curated information environment” (Wood, 2019, p. 573) of social media, the in-built architecture that structures social media use. Identifying key nodes and influencers residing within a network who occupy a more significant role in information diffusion (Wood et al., 2019) holds the potential to identify information flow to institutional social media accounts. This chapter compliments the rhizomatic model of informal justice-seeking through an identification of the structural relations that underpinned online users' informal justice response to the Broad incident. Methodology Our study utilized a parallel mixed methods research design that combined a quantitative SNA and qualitative ATA (Borgatti, Everett, & Johnson, 2018) to establish a structural understanding of the social media response to the 2017 Broad incident. These methods enabled the assessment of differing components of the phenomenon, enhancing its interpretability. We collected and analyzed these quantitative and qualitative data sources separately before integrating them in the second phase of the project (Creswell & Clark, 2007). To begin this process, an SNA was conducted to develop a quantitative representation of different user types with a corpus of data relating to an incident of IBSA. SNA enabled the visualization of relational ties between social actors – in this case individual Twitter users, such as journalists, institutional news media accounts, and personal Twitter users. This included interactions such as liking or retweeting user content, and follower/followee relationships. These ties could be typologized through user type differentiation established by Beguerisse-Díaz, Garduno-Hernández, Vangelov, Yaliraki, and Barahona (2014) in their SNA of the London riots:

This article reflects on part of a three-year battle over the redevelopment of an iconic Melbourne music venue, the Palace-Metro Nightclub (the Palace), involving the tactical use of Facebook Page data at trial. We were invited by the Save the Palace group, Melbourne City Council and the National Trust of Australia to provide Facebook Page data analysis as evidence of the social value of the venue at an appeals trial heard at the Victorian Civil Administration Tribunal (VCAT) in 2016. We take a reflexive ethnographic approach here to explore the data production, collection and analysis processes as these represent and constitute a “data public”.Although the developers won the appeal and were able to re-develop the site, the court accepted the validity of social media data as evidence of the building’s social value (Jinshan Investment Group Pty Ltd v Melbourne CC [2016] VCAT 626, 117; see also Victorian Planning Reports). Through the case, we elaborate on the concept of data publics by considering the “affordising” (Pollock) processes at play when extracting, analysing and visualising social media data. Affordising refers to the designed, deliberate and incidental effects of datafication and highlights the need to attend to the capacities for data collection and processing as they produce particular analytical outcomes. These processes foreground the compositional character of data publics, and the unevenness of data literacies (McCosker “Data Literacies”; Gray et al.) as a factor of the interpersonal and institutional capacity to read and mobilise data for social outcomes.We begin by reconsidering the often-assumed connection between social media data and their publics. Taking onboard theoretical accounts of publics as problem-oriented (Dewey) and dynamically constituted (Kelty), we conceptualise data publics through the key elements of a) consequentiality, b) sufficient connection over time, c) affective or emotional qualities of connection and interaction with the events. We note that while social data analytics may be a powerful tool for public protest, it equally affords use against public interests and introduces risks in relation to a lack of transparency, access or adequate data literacy.Urban Protest and Data Publics There are many examples globally of the use of social media to engage publics in battles over urban development or similar issues (e.g. Fredericks and Foth). Some have asked how social media might be better used by neighborhood organisations to mobilise protest and save historic buildings, cultural landmarks or urban sites (Johnson and Halegoua). And we can only note here the wealth of research literature on social movements, protest and social media. To emphasise Gerbaudo’s point, drawing on Mattoni, we “need to account for how exactly the use of these media reshapes the ‘repertoire of communication’ of contemporary movements and affects the experience of participants” (2). For us, this also means better understanding the role that social data plays in both aiding and reshaping urban protest or arming third sector groups with evidence useful in social institutions such as the courts.New modes of digital engagement enable forms of distributed digital citizenship, which Meikle sees as the creative political relationships that form through exercising rights and responsibilities. Associated with these practices is the transition from sanctioned, simple discursive forms of social protest in petitions, to new indicators of social engagement in more nuanced social media data and the more interactive forms of online petition platforms like change.org or GetUp (Halpin et al.). These technical forms code publics in specific ways that have implications for contemporary protest action. That is, they provide the operational systems and instructions that shape social actions and relationships for protest purposes (McCosker and Milne).All protest and social movements are underwritten by explicit or implicit concepts of participatory publics as these are shaped, enhanced, or threatened by communication technologies. But participatory protest publics are uneven, and as Kelty asks: “What about all the people who are neither protesters nor Twitter users? In the broadest possible sense this ‘General Public’ cannot be said to exist as an actual entity, but only as a kind of virtual entity” (27). Kelty is pointing to the porous boundary between a general public and an organised public, or formal enterprise, as a reminder that we cannot take for granted representations of a public, or the public as a given, in relation to Like or follower data for instance.If carefully gauged, the concept of data publics can be useful. To start with, the notions of publics and publicness are notoriously slippery. Baym and boyd explore the differences between these two terms, and the way social media reconfigures what “public” is. Does a Comment or a Like on a Facebook Page connect an individual sufficiently to an issues-public? As far back as the 1930s, John Dewey was seeking a pragmatic approach to similar questions regarding human association and the pluralistic space of “the public”. For Dewey, “the machine age has so enormously expanded, multiplied, intensified and complicated the scope of the indirect consequences [of human association] that the resultant public cannot identify itself” (157). To what extent, then, can we use data to constitute a public in relation to social protest in the age of data analytics?There are numerous well formulated approaches to studying publics in relation to social media and social networks. Social network analysis (SNA) determines publics, or communities, through links, ties and clustering, by measuring and mapping those connections and to an extent assuming that they constitute some form of sociality. Networked publics (Ito, 6) are understood as an outcome of social media platforms and practices in the use of new digital media authoring and distribution tools or platforms and the particular actions, relationships or modes of communication they afford, to use James Gibson’s sense of that term. “Publics can be reactors, (re)makers and (re)distributors, engaging in shared culture and knowledge through discourse and social exchange as well as through acts of media reception” (Ito 6). Hashtags, for example, facilitate connectivity and visibility and aid in the formation and “coordination of ad hoc issue publics” (Bruns and Burgess 3). Gray et al., following Ruppert, argue that “data publics are constituted by dynamic, heterogeneous arrangements of actors mobilised around data infrastructures, sometimes figuring as part of them, sometimes emerging as their effect”. The individuals of data publics are neither subjugated by the logics and metrics of digital platforms and data structures, nor simply sovereign agents empowered by the expressive potential of aggregated data (Gray et al.).Data publics are more than just aggregates of individual data points or connections. They are inherently unstable, dynamic (despite static analysis and visualisations), or vibrant, and ephemeral. We emphasise three key elements of active data publics. First, to be more than an aggregate of individual items, a data public needs to be consequential (in Dewey’s sense of issues or problem-oriented). Second, sufficient connection is visible over time. Third, affective or emotional activity is apparent in relation to events that lend coherence to the public and its prevailing sentiment. To these, we add critical attention to the affordising processes – or the deliberate and incidental effects of datafication and analysis, in the capacities for data collection and processing in order to produce particular analytical outcomes, and the data literacies these require. We return to the latter after elaborating on the Save the Palace case.Visualising Publics: Highlighting Engagement and IntensityThe Palace theatre was built in 1912 and served as a venue for theatre, cinema, live performance, musical acts and as a nightclub. In 2014 the Heritage Council decided not to include the Palace on Victoria’s heritage register and hence opened the door for developers, but Melbourne City Council and the National Trust of Australia opposed the redevelopment on the grounds of the building’s social significance as a music venue. Similarly, the Save the Palace group saw the proposed redevelopment as affecting the capacity of Melbourne CBD to host medium size live performances, and therefore impacting deeply on the social fabric of the local music scene. The Save the Palace group, chaired by Rebecca Leslie and Michael Raymond, maintained a 36,000+ strong Facebook Page and mobilised local members through regular public street protests, and participated in court proceedings in 2015 and February 2016 with Melbourne City Council and National Trust Australia. Joining the protesters in the lead up to the 2016 appeals trial, we aimed to use social media engagement data to measure, analyse and present evidence of the extent and intensity of a sustained protest public. The evidence we submitted had to satisfy VCAT’s need to establish the social value of the building and the significance of its redevelopment, and to explain: a) how social media works; b) the meaning of the number of Facebook Likes on the Save The Palace Page and the timing of those Likes, highlighting how the reach and Likes pick up at significant events; and c) whether or not a representative sample of Comments are supportive of the group and the Palace Theatre (McCosker “Statement”). As noted in the case (Jinshan, 117), where courts have traditionally relied on one simple measure for contemporary social value – the petition – our aim was to make use of the richer measures available through social media data, to better represent sustained engagement with the issues over time.Visualising a protest public in this way raises two significant problems for a workable concept of data p

Text data from social media and networks are ubiquitous and are emerging at a high rate. Tackling these bulky text data has become a challenging task and an important field of research. The mining of text data and examining it with the help of several clustering techniques, classification techniques, and soft computing methods has been studied in a comprehensive manner in the past. This chapter focuses mainly on the hybrid techniques that have been used to mine textual data from social networks and media data. Social networks are considered a profuse source of viewpoints and outlooks of the public on a worldwide scale. An enormous amount of social media data is produced on a regular basis, generated because of the communication between the users who have signed up for the various social media platforms on several topics such as books, movies, politics, products, etc. The users vary in terms of factors such as viewpoints, scenarios, geographical situations, and many other settings. If mined efficiently, the data have the potential to provide a helpful outcome of an exegesis of social quirks and traits. This chapter offers a detailed methodology on how data mining, especially text mining, is applied to social networks in general. Furthermore, it goes on to introduce the traditional models used in mining the various hybrid methodologies that have evolved and make a comparative analysis. We also aim to provide the future scope and research studies present in this field with all possible new innovations and their applications in the real world.

COVID-19 Could Change the Way We Respond to the Opioid Crisis-for the Better.

Exploring the Multiple Roles of Acupuncture in Alleviating the Opioid Crisis.

Climate change communication increasingly unfolds within digital environments, where social media platforms such as Twitter play a pivotal role in shaping public discourse (Papacharissi, 2015). This study combines Social Network Analysis (SNA) and Discourse Analysis (DA) to explore how climate change is discussed and structured through Twitter interactions. A dataset of tweets mentioning Greta Thunberg and Donald Trump—the two most frequently mentioned figures identified through network centrality measures—was analyzed. Using Gephi software, network properties such as modularity, degree centrality, and graph diameter were evaluated and visualized through the Force Atlas layout. The findings reveal a fragmented but interconnected network structure, with modular clusters aligned with political, activist, and organizational affiliations. Discourse analysis of the tweets highlights contrasting narrative strategies: while Greta Thunberg is framed through language of solidarity, urgency, and mobilization, Donald Trump is predominantly referenced through oppositional and critical discourse. These patterns exemplify the dynamics of connective action in digital environments, where personal engagement drives collective narratives (Bennett & Segerberg, 2012). Overall, the results suggest that Twitter reflects and amplifies emotional and ideological currents within the climate change debate, fostering both polarization and solidarity across different stakeholder communities. This study contributes to understanding the complex interplay between digital communication structures and climate change narratives.

Closing the global pain divide: balancing access and excess

Opioid Stewardship in Cardiac Anesthesia Practice

The growing availability of big data spontaneously generated by social media platforms allows us to leverage natural language processing (NLP) methods as valuable tools to understand the opioid crisis. We aimed to understand how NLP has been applied to Reddit (Reddit Inc) data to study opioid use. We systematically searched for peer-reviewed studies and conference abstracts in PubMed, Scopus, PsycINFO, ACL Anthology, IEEE Xplore, and Association for Computing Machinery data repositories up to July 19, 2022. Inclusion criteria were studies investigating opioid use, using NLP techniques to analyze the textual corpora, and using Reddit as the social media data source. We were specifically interested in mapping studies' overarching goals and findings, methodologies and software used, and main limitations. In total, 30 studies were included, which were classified into 4 nonmutually exclusive overarching goal categories: methodological (n=6, 20% studies), infodemiology (n=22, 73% studies), infoveillance (n=7, 23% studies), and pharmacovigilance (n=3, 10% studies). NLP methods were used to identify content relevant to opioid use among vast quantities of textual data, to establish potential relationships between opioid use patterns or profiles and contextual factors or comorbidities, and to anticipate individuals' transitions between different opioid-related subreddits, likely revealing progression through opioid use stages. Most studies used an embedding technique (12/30, 40%), prediction or classification approach (12/30, 40%), topic modeling (9/30, 30%), and sentiment analysis (6/30, 20%). The most frequently used programming languages were Python (20/30, 67%) and R (2/30, 7%). Among the studies that reported limitations (20/30, 67%), the most cited was the uncertainty regarding whether redditors participating in these forums were representative of people who use opioids (8/20, 40%). The papers were very recent (28/30, 93%), from 2019 to 2022, with authors from a range of disciplines. This scoping review identified a wide variety of NLP techniques and applications used to support surveillance and social media interventions addressing the opioid crisis. Despite the clear potential of these methods to enable the identification of opioid-relevant content in Reddit and its analysis, there are limits to the degree of interpretive meaning that they can provide. Moreover, we identified the need for standardized ethical guidelines to govern the use of Reddit data to safeguard the anonymity and privacy of people using these forums.

Orange County Sues Opioid Drug Makers: Suit Broadens Assault on Spiraling Opioid Abuse

[EMBARGOED UNTIL 08/01/2025] Social media, for the past twenty years and especially post-pandemic, has a major impact on health information consumers as well as on health information sharing. With more and more consumers spending greater time on social media and mobile apps, it is destined to have an indisputable influence on personal healthcare decision-making and choices that consumers make about taking care of their health. In a PwC poll, 41 percent of respondents said they made their decision on a certain physician, hospital, or medical facility based on information they found on social media. Social media sites can serve as focal points for tracking online dialogues about diseases where users engage in inquiries, posting personal accounts, and debating subjects like diabetes and cancer. Studies have shown that social media content analysis from social media websites and apps can provide unique viewpoints on chronic diseases, the accessibility of treatment, and their consequences. This can lead to an enhanced understanding of topics as it is useful in detecting systemic obstacles and disparities, as well as informing focused initiatives, lobbying efforts, and legislative changes. Further, the enhancement of social media information retrieval using social network analysis tools is an innovative and user-friendly method to unveil contemporary patterns impacting the domain of chronic illnesses in chronic and public health discussions. There are hardly any studies that use social network analysis to study chronic disease information on social media channels. The dissertation follows disease conversations by using social media network analysis to examine narratives about managing diabetes and cancer, COVID-19 and health equity, and health insurance. We demonstrate that using this technique, researchers can keep an eye on current conversations and spot reoccurring themes. Real-time monitoring can shed light on topics such as treatment outcomes, public perceptions, and obstacles to disease management with amazing speed. We believe that systematically carrying out social network analysis could help to respond to and design policy measures to fix coverage gaps and enhance service accessibility guided by social media insights. Positive changes in public health can be facilitated while supporting community engagement, promoting health equity, and targeted interventions in real time. This dissertation emphasizes how social media content analysis can revolutionize research on chronic diseases and public health conversations. Our plan for creating a dashboard with state-by-state social media live links related to chronic illnesses and rare diseases is one of our ongoing and upcoming projects. This dashboard will be a valuable tool for monitoring and accessing public health issues and revealing the burden of chronic diseases online. It could provide public health agencies the means to incorporate a comprehensive strategy for addressing the difficulties seen with chronic diseases in the digital age.

PurposeAs one of the buzzwords in the present age with considerable impacts in tertiary institutions, social media use in online teaching, learning and information dissemination have been extensively discussed in extant literature. This paper aims to explore the existing campus sustainability appraisal (CSA) tools to identify the length at which social media has been used, especially in environmental sustainability indicators’ selection and empirical verification.Design/methodology/approachThe methodology is mainly based on a desktop study involving comprehensive review and content analysis of existing CSA tools’ documents. Webpage content analysis of selected sustainability monitoring and tracking system in higher education institutions was also conducted.FindingsThe tools' content analysis reveals insufficient utilization of social media data and platforms in campus sustainability environmental-dimension indicators selection. To bridge this identified research gap, social media user-generated content for appraising the campus-wide environmental sustainability indicators preference in tertiary institutions was proposed.Practical implicationsThe adoption and modification of this study’s proposed approach by tertiary institutions, especially in sub-Saharan African countries, could help address most campus-wide environmental challenges raised, commented on and discussed on social media.Originality/valueThis study contributes to knowledge gaps by revealing the extent of social media utilization in extant tools. With the expanding utilization of different social media platforms by various tertiary institutions worldwide, their administrators' responsibility is to put these social media data into fair use.

People with opioid use disorder (OUD) have very high tobacco use rates (75-95%) that are rarely addressed in opioid treatment programs (OTPs) where they receive care. This is a missed opportunity to leverage the benefits of concurrent tobacco cessation to facilitate OUD recovery and prevent tobacco-related cancer disparities. Based on Social Cognitive Theory, OUTPACE (Opioid Use Treatment Programs Advancing Cessation Efforts) Tobacco is a comprehensive tobacco-free workplace program that provides policy and workflow guidance, specialized training, and resources to bolster OTPs’ capacity to screen for tobacco use and briefly intervene with referral to a Quitline for care. Here, we describe its implementation. Methods: We partnered with an OTP with 40 staff working in 3 clinic locations serving 295 patients yearly across 4 Texas counties (1 rural and 2 partially rural, collectively serving 4 medically underserved areas). Data on staff’s pre-implementation tobacco-related policies and practices were collected via e-surveys and interviews to guide implementation, using EPIS (episframework.com). Implementation strategy bundles aided uptake of OUTPACE Tobacco’s core components. Program implementation spanned 2024-2025 and was evaluated quantitively and qualitatively; sustainment is ongoing. Results: At pre-implementation, OTP tobacco screening and intervention capacity was poor with 50% of 33 responding staff asking patients about tobacco use and only 4.2-29% advising them to quit, assessing quit interest, assisting quitting, and following up. Staff rated their tobacco intervention knowledge at 5.4 (SD=2.7) on a 1 to 10 scale. About 42% received past year training on tobacco use care and only 12% favored concurrent opioid and tobacco treatment. Barriers included lack of training (50%), patient education materials (50%), and referral resources (36%). However, 88% of staff wanted training and, overall, agreed that OUTPACE Tobacco was acceptable, appropriate, and feasible for implementation. Qualitative findings contextualize and support survey responses. During implementation, all staff were trained on the harms of tobacco use and how to help patients quit, exhibiting a 47% knowledge gain (p<0.001). The OTP director completed tobacco treatment specialist training and a train-the-trainer program. A tobacco-free workplace policy was implemented and >4,000 patient education and >2,000 provider nudge materials were provided. Staff were trained on HIPAA-secure Quitline referral methods, which are ongoing; engaged callers may receive up to 12 counseling calls and 16 weeks of dual NRT across 2 quit attempts a year. Mixed methods implementation findings and lessons learned will be shared. Conclusions: Implementation of OUTPACE Tobacco in a high-need OTP provides proof-of-concept for the uptake of a multi-component tobacco-free workplace intervention despite initial barriers. These findings suggest the usefulness of OUTPACE Tobacco implementation in OTPs to address critical gaps in tobacco-related care that put patients with OUD at risk for cancer disparities. Citation Format: Asfand B. Moosa, Maggie Britton, Isabel Martinez Leal, Hannah Wani, Tzuan A. Chen, Diane M. Beneventi, Jennifer A. Minnix, Maher A. Karam-Hage, Paul M. Cinciripini, Mikal Zere, Marcy Zere, Douglas Thornton, Lorraine R. Reitzel. Preventing tobacco-related cancer disparities among opioid use treatment program stakeholders: A case study of a tailored tobacco-free workplace program implementation with reach to rural/medically underserved areas of Texas [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr B014.

To determine which social media analytics tools, techniques, and platforms were developed in recent times, this paper reviews tools, techniques, and platforms related to social media analytics. In this paper, we talk about the tools used to deal with various social media data (social networking, media, etc.). In the past decade, there has been advancement in the technologies used to deal with social media as there has been an increase in the number of people using social media to share information and also the development of the new social media platforms that have let to increase in the amount of data that we have to deal with. Social media platforms have a considerable number of users across the world, which is overgrowing. These people are sharing information through these sources. There is a large quantity of social data comprising of data related to users, videos, web-based relations, and interactions, etc. which needs to be analyzed. Therefore analyzing social media data has become a significant activity for researchers, mainly due to the availability of the web-based API from social media platforms like twitter, facebook [1], Gmail, etc. This has also led to the development of data services, software tools for analyzing social media data. In this paper, there is a detailed review of the leading software tools and techniques that are used for scraping, cleaning, and analyzing social media data.

Despite an abundance of public discourse about the opioid crisis in the media, there is little research characterizing opioid-related content on TikTok, a popular video-based social media platform. This study sought to examine how opioids are portrayed on TikTok. This study used mixed methods to analyze top opioid-related posts marked with the hashtag "#opioids" collected in May 2023. "Holistic coding" was used to topically categorize multimedia content in posts and to quantify the frequency of mentioning opioid-related content areas (e.g., overdose, pain, fentanyl). Template analysis methods were then used to develop themes. A total of 115 posts were analyzed. The most frequently used opioid-related topic codes include prescription opioids (58.3% of posts), pain (47.0%), overdose (35.7%), and fentanyl (34.8%). Posts were most commonly about challenges to accessing prescription opioids for pain management (37.4%), opioid policy (36.5%), and negative consequences of using opioids (32.2%). Qualitative analysis yielded themes about the potential dangers associated with using opioids, treatment and recovery from opioid use disorder, and barriers to obtaining prescription opioids for pain management. This study revealed polarizing opinions within opioid-related content on TikTok. The two main stances, dangers of nonmedical opioid use and advocacy for the availability of prescription opioids for pain management, represent nationwide tensions between the opioid and chronic pain crises. The vast audience TikTok garners presents an opportunity for disseminating opioid education, harm-reduction strategies, and treatment options for opioid use disorder that were largely absent among the posts analyzed.