Justice on the Digitized Field: Analyzing Online Responses to Technology-Facilitated Informal Justice through Social Network Analysis

The Emerald International Handbook of Technology-Facilitated Violence and Abuse

ISBN: 978-1-83982-849-2, eISBN: 978-1-83982-848-5

Publication date: 4 June 2021


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.



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, Leeds, pp. 689-709. https://doi.org/10.1108/978-1-83982-848-520211051



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.


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.


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:

  1. What are the structural and intermedia features of Twitter users' responses to IBSA?

  2. 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.


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:

  • References: Typically, institutional accounts, important sources of content or well-known personalities with many followers who follow few accounts.

  • Mediators: Users who interact with … leader categories (i.e., they follow and are followed by high-profile accounts), as well as with nodes in the Listener categories below.

  • Listeners: Accounts with few followers (within this network, not necessarily over the whole of Twitter) who follow mostly Reference nodes. Within this particular network, they can be considered as passive recipients of mainstream content (p. 7).

In our model, these roles are established through an observation of the mutual influence of users within different demographics. This can be traced through the direction of their relationships – ingoing or outgoing – to either indicate a follower–following relationship or tweet interaction. For example, a node or user situated within a network who is followed by a large number of users, who follows fewer users, and has high rates of tweet engagement indicated through network edges would be typologized as a Reference user. This position is often occupied by journalists or broadcasters.

SNA is underpinned by the assumption that examining the structure of networks allows for a better understanding of the network members' behavior and beliefs. SNA enables us to examine how relational ties between members of a network provide pathways for the flow of information and sentiment, which may shape members beliefs, perceptions, and actions (Knoke & Yang, 2008). For us, this translated to observing the structure of the network produced within a search term, including the differing demographics of users, their relational ties, and the subnetworks of identified users. Using Gephi, a social network visualization software, alongside data captured using the scraping tool NodeXL, a network of Twitter users appearing within the search term “Nathan Broad” was established.

Structuring analysis and data collection around a singular search term – “Nathan Broad” – occurred as a result of the lack of informal “hashtag” or key phrases associated with the event. Searching Broad's name informally, or other associated terms, generated a large body of irrelevant Twitter content, which was avoided by using the specific search term. Another caveat on project scope was that the online engagement following a local Australian incident of IBSA generated a lower engagement dataset than what would be expected from a study observing an internationally recognized celebrity incident.

These limitations were in part countered through the use of an ATA of every tweet which featured the term “Nathan Broad” from the October 1, 2017 to the November 4, 2017 (n = 629). ATA enabled the identification of patterns or themes independent of a specific theoretical framework. The time period the tweets were sampled from encompassed the initial sharing of the image and the media response that followed Nathan Broad's naming. The tweets were procured by copying all data from the complete Twitter search into a text file, representing every tweet within the relevant search criteria. This sample does not represent the full Twitter response to Broad, but instead just those who chose to refer to him by his full name and allowed their tweets to be accessible in Twitter's public search function. Twenty-three tweets were excluded due to irrelevance. 3 The final sample included 629 tweets which were then coded and analyzed using the qualitative data analysis program NVivo.

As noted earlier, this research design provides a new contribution to the current corpus of TFV and IBSA analysis as it specifically demarcates the social phenomenon embedded within electronic infrastructures (Venturini, Bounegru, Gray, & Rogers, 2018), such as Twitter, through the use of a mixed methods research design. To operationalize our considerations of “infrastructures,” we attuned our line of inquiry to Twitter's follower–following relationships via Beguerisse-Díaz et al. (2014)'s typology of Twitter users. This allowed us to observe how Twitter as a platform facilitates and structures sentiment diffusion among differing user types in relation to IBSA.


The Broad incident was unique in its mobilization of a large population of Twitter users who spoke out against Broad and the institutions responsible for his sanction. These counterhegemonic discourses formed the basis of a phenomenon known as online informal justice-seeking – the utilization of social media to contest existing institutional responses to crime (Powell, 2015). In producing a tiered account of the informal justice-seeking response by Twitter users to Broad's naming in the media, we were able to present a unique contribution to TFV and IBSA studies.

Finding One: Structuring Communicative Flows

Our analysis began by first establishing a preliminary understanding of the demographic and sentiment breakdown within the dataset of tweets specific to Nathan Broad from late October to early November 2017. Users were classified into the user types established within Beguirisse-Díaz et al.’s (2014) typology, with a differentiation of users based on their generation and reception of content and information. As this initial analysis was not aided by an automated data scrape differentiating user types, the follower–followee relationship could not be identified at this point in the analysis. Instead, a Listener–Reference dichotomy was utilized based on intuitive coding of screen name, verification status, tweet content, and engagement. 4 Additionally, tweets were coded intuitively based on their sentiment toward Broad's identification and punishment. Tweets that sought to identify Broad as the perpetrator of a sex crime, either literally or through the use of terms denoting shame and humiliation, were coded negatively alongside tweets criticizing institutional responses. 5 Passive observation of the crime and resharing of news media were coded neutrally. Finally, tweets that sought to blame the victim, neutralize the harm of Broad's actions, or minimize Broad's responsibility were coded positively. This allowed for the production of numerical representations of the differing spread of sentiment within the dataset, and which user types they aligned to, as seen in Fig. 40.1.

Fig. 40.1. 
Differentiation in Sentiment and Demographic Responses among Twitter Users within the “Nathan Broad” Search Term.

Fig. 40.1.

Differentiation in Sentiment and Demographic Responses among Twitter Users within the “Nathan Broad” Search Term.

In Fig. 40.1, Reference accounts made up 43% of the dataset (n = 270), while Listeners made up 56% (n = 352). 6 Use of the search term “Nathan Broad” excluded the acquisition of any tweets that were made about the incident that did not quote Broad's name in full. Consequently, no transferable conclusions can be drawn from the specific ratio of Listeners and Reference users within this dataset. Among Reference users, a shift in sentiment regarding the incident could be observed as time progressed, as reporting and descriptions of the event in the dataset shifted from largely sentiment-neutral to negative, criticizing Broad and his actions. “Reference” media narratives regarding IBSA can be positioned within broader literature on the historical minimization of sexual abuse victims by the media and the institutions aligned with perpetrators (Waterhouse-Watson, 2013). More specifically, Broad's position as an athlete would historically grant him “narrative immunity” within representations of his behavior, a process which seeks to deflect blame from the perpetrators of sexual abuse and alleviate players of responsibility (Waterhouse-Watson, 2013, p. 5). Our findings challenged this, observing a shift from neutral to negative representations of Broad.

The spread of sentiment among Listeners echoed this trend of negative representations of Broad, a sympathetic response to the victim, and an acknowledgment of the harms generated by the image's release. Preliminary themes included frustration at the RFC and the AFL for the lenient sanction Broad received, and confusion over why Broad had not been apprehended by police despite the existence of laws penalizing his behavior within Victoria (Victorian Parliament, 2007). The breadth and depth of this sentiment within this dataset indicates an informal justice-seeking response to the Broad incident by some Twitter users, where the communicative space of Twitter enabled users to project their response to the incident to a wide social media audience (Powell, 2015). This did not occur without victim-blaming and neutralization techniques among 15% of users (n = 94), echoing a sentiment that would be expected from some fans and supporters of AFL as an all-male and patriarchal subculture that holds significant power in legitimizing sexual harms against women (DeKeseredy & Schwartz, 2016). Finally, the majority of neutral responses involved individuals resharing neutral news media – an expected product of the retweeting mechanism built into Twitter's platform.

Communication technologies such as social media allow for the production of harms such as IBSA (see Henry, Flynn, & Powell, 2019; Powell, Scott, Flynn, & Henry, 2020). However, they have also enabled users to challenge institutional responses to these crimes through informal justice-seeking (Powell, 2015). Our study sought to identify a structure upon which the flow of sentiment could be observed – to demarcate the way different users produced, directed, and interrupted neutral or sympathetic discourses identified in earlier paragraphs. To do this, we shift our attention to the SNA dataset featuring individual actors engaging with the Broad incident via Twitter.

To ground this process, seven major institutional accounts were identified as Reference users within this network. This occurred on the basis of verification status and follower count (>30,000). These accounts, pseudonymized to accord with ethics requirements, 7 formed the vast majority of incoming edge connectivity within the network – where edges indicate instances of interaction and follower/followee relationship on Twitter. Each node, or user, represented either a prominent institutional account within AFL or a major Australian broadcaster.

Positioning the role of Reference users within this network enabled an identification of Mediator users – “users who interact with … leader categories (i.e., they follow and are followed by high-profile accounts), as well as with nodes in the Listener categories” (Beguerisse-Díaz et al., 2014, p. 7). This process involved an observation of the users within this network, as the primary determinant of a Mediator role was incoming edges from Reference users. These users were identified as the group that was followed by any of the seven identified Reference accounts, rendering their sentiment visible to institutional users. Out of a total 25 outgoing edges among the Reference accounts, nine were identified as “personal” Twitter users. Their identification allowed for a stratified display of each user type situated within the network, as seen in Fig. 40.2.

Fig. 40.2. 
Distribution of References, Mediators, and Listeners within Network. Note: Orange edges appearing on certain nodes are an artifact of the data gathering process and should be disregarded.

Fig. 40.2.

Distribution of References, Mediators, and Listeners within Network. Note: Orange edges appearing on certain nodes are an artifact of the data gathering process and should be disregarded.

At this scale, Mediators are seen to permeate varying points of the network and each node was established via a clustering algorithm. Node size relates specifically to their “betweenness centrality” – the number of times each node acts as a bridge along the shortest path in a network, thus allowing for a quantification of the dispersal of information among networked individuals (Freeman, 1977). The six major institutional accounts appear centrally within the network and occupy a vast majority of the edge density (201 edges of a total 327). 8 This established stratification between Reference, Mediator, and Listener roles guided the investigation into the specific structure of interactions within this network.

A valuable method for examining the structure of user relations within SNA was through consideration of the subcommunities residing within the larger network. Schmidt (2014) details the role of these groups among Twitter users in developing communities of practice, wherein social rules are produced and upheld. These communities are built by and for the users who utilize Twitter for personal networking and content-sharing – those identified as Listeners in these networks. Having established flows of information between Mediators to Reference accounts, the next step was to consider the differing forms of communication between Listeners and Mediators. These users were not as easily differentiated via follower count, and therefore a consideration of their place within the network beyond the influence of Reference accounts can be seen in Fig. 40.3.

Fig. 40.3. 
Listener–Mediator Network Prior to Community Detection.

Fig. 40.3.

Listener–Mediator Network Prior to Community Detection.

With the vast majority of network edges removed, Fig. 40.3 presents a network of significantly lower global connectivity. However, the modularity ranking of this network tells a different story. Modularity statistics allow for a numerical ranking of the typology of interconnected nodes in a network, and their decomposition into subcommunities with high levels of connectivity (Blondel, Guillaume, Lambiotte, & Lefebvre, 2008). Within the larger social network (inclusive of Reference accounts), the modularity ranking sat at 0.234 (on a scale of 0–1). This is small in comparison to the Mediator network, which had a modularity ranking of 0.603. This Mediator network is illustrated in Fig. 40.4, where a clustering algorithm is applied to reveal five distinct subnetworks contained within the larger network displayed in Fig. 40.3. This network excluded six nodes and the smaller secondary network due to a lack of connectivity to the larger network.

Fig. 40.4. 
Listener–Mediator Network Following Community Detection via ForceAtlas2 Clustering Algorithm and Size Differentiation Based on Betweenness Centrality. Note: Nodes JN, J6, 7S, P5, T7, and BI excluded due to no connection with larger network.

Fig. 40.4.

Listener–Mediator Network Following Community Detection via ForceAtlas2 Clustering Algorithm and Size Differentiation Based on Betweenness Centrality. Note: Nodes JN, J6, 7S, P5, T7, and BI excluded due to no connection with larger network.

This smaller network solely features people who utilized Twitter purely for personal use, and a number of observations can be drawn from this network based on this composition. Modular subcommunities within networks such as these represented groups wherein “information, interest and influence is propagated, retained and reinforced” (Beguerisse-Díaz et al., 2014, p. 2). Several users that occupied key positions in these networks – identified by node size (betweenness centrality) – happened to be Mediators. Accounts such as TD and RD appeared centrally within modular subcommunities distinct from the wider network. This smaller network was also unified by the user JD, who shared a tweet which received significant engagement, with many users—both those connected and those disconnected from the wider network—retweeting or mentioning user JD. Multiple Mediator accounts engaged with this tweet, diffusing the sentiment beyond this user both to other subcommunities and to the feeds of Reference accounts.

Several conclusions can be drawn from a structural analysis of this network. The first involves the substantial modularity of the Listener/Mediator subnetwork. The observation of five distinct subcommunities that were only well connected via a general trend of following Reference accounts suggests that prominent institutional media bridged the gap between these groups. The potential for many-to-many communication was also observed as a bridging factor, drawing together multiple distinct subnetworks that reshared and engaged with a prominent tweet from a Listener within the network. Both of these forms of communication operated parallel to one another, producing relationships and interactions that dispersed information through the network.

A second observation concerned the following patterns of Reference accounts. There seemed to be no identifiable characteristic that differentiated Mediator accounts in terms of their strength within the network. This lack of discernible difference means that Mediator accounts permeated a variety of different positions within the larger Twitter network, occupying multiple different subcommunities and interacting with multiple different streams of sentiment.

Drawing from this, we propose that in this network Mediator accounts are utilized by Reference accounts as “sounding boards” upon which public sentiment is observed and acted upon. While these Reference accounts do not explicitly engage with the public, they exist as important sources of content upon which the public rely. Mediator users, and their position between Listeners and References, offer an insight into how Twitter users’ responses to an incident of IBSA can be hierarchized. We argue that the identification of these user types provides utility and nuance when conducting thematic analysis of social media responses to an incident of IBSA, as we demonstrate in the following section.

Finding Two: Counterhegemonic Narratives

Above, we established the structural and intermedia features of the Twitter response to the Broad incident. These findings provided a framework to analyze the spread of responses to Broad – both his actions and the sanction he received. A major theme observed within the Twitter responses to Broad was an outpouring of sympathy toward the victim, and a generalized disdain directed toward Broad and the sanction he received from RFC. Viewed collectively, we propose that these tweets made up a counterpublic of individuals seeking to contest the sanction handed down by RFC, and the incident which led to it. Counterpublics provide a space for individuals to challenge the monopoly of speech held by old media, as well as to discuss and challenge incidents of sexual violence contrary to established norms (Salter, 2013). The assignment of blame and guilt was relatively transparent in the Broad incident, a factor that may have contributed to the breadth of sympathetic responses to the victim. Instead of leading to a reduction in responses to the incident due to a “clean case,” this straightforwardness instead empowered individuals to voice an array of counterdiscourses criticizing the culture and institutions responsible for the incident, in this case the RFC and AFL. Users expressing this sentiment fell within the “Listener” category – personal Twitter users and passive recipients of mainstream content.

Most notable among these counterdiscourses was an immense frustration at the RFC response to the incident – Broad's three-week sanction at the start of the 2018 AFL season. Numerous tweets suggested that Broad should have been delisted or fired:

nathan broad retire bitch

0 replies 1 retweet 6 likes

Richmond Football Club should have fired Nathan Broad, not suspended him. What a slap on the wrist for a sex crime. Disgraceful.

0 replies 0 retweets 1 like

Some called into question RFC and the AFL's commitment to gender equality following the verdict:

Replying to @Richmond_FC <https://Twitter.com/Richmond_FC>

you can't call yourself 'a club committed to gender equality' until nathan broad is fired - what a disgrace

3 replies 3 retweets 11 likes

What a crock! Nathan Broad gets a 3 game suspension for committing a crime. #AFL disappointingly weak again on respect towards women

0 replies 0 retweets 2 likes

Users were also persistent in their recognition of the harms of the image and the humiliation faced by the victim:

Nathan Broad from Richmond gets 3 game suspension. Young woman gets smeared for life.

0 replies 5 retweets 4 likes

So very disappointing @AFL #Nathan Broad-3/52, woman-humiliated. poor decision making and Leadership @Richmond_FC http://www.abc.net.au/news/2017-10-30/richmond-player-nathan-broad-named-over-topless-photo/9098712

1 reply 0 retweets 1 like

This outcry, the result of a frustrated supporter base disillusioned with the hypocrisy of the RFC's decision, spanned the full breadth of the dataset and was largely unchallenged by other users.

Another notable theme was the acknowledgment of Broad's actions as criminal, warranting intervention by the criminal justice system:

Since he's admitted to it, I'd have thought Nathan Broad can be arrested now.

2 replies 9 retweets 38 likes

Nathan Broad: 'I let down a young woman I cared about.'

You committed a CRIME against her.

1 reply 1 retweet 3 likes

These tweets explicitly associated Broad's actions with laws that criminalize IBSA. The tweets also highlight a confusion at the disjuncture between the existence of laws targeting IBSA and institutions' responsibility to act upon those laws. Preexisting literature has addressed the challenges of prosecuting the distribution and spread of nonconsensual sexual imagery, including the difficulty in proving the originator of the image carried malicious intent, and the diffusion of responsibility to the wider social media audience who shared and reshared the image (Flynn & Henry, 2019; Henry, Flynn, & Powell, 2018; Powell, 2015). In this case, while the victim did not seek to press charges, users were insistent that sex offense charges should have been applied. Instead, the responsibility for punishing Broad was held by his football club, and as noted earlier, some users shared a view that the punishment by RFC should have delivered justice with a harsher sanction.

The discourses circulated by Listeners provide valuable insight into social media users' frustration with inadequate institutional responses to IBSA. They also provided a substrate for operationalizing the Listener/Mediator/Reference user dichotomy established within previous findings. To do this, a framework of intermedia agenda-setting was applied to assess how the responses outlined earlier were mirrored by Reference accounts tweeting about Broad's actions. Sexual misconduct perpetrated by footballers is often represented as an inevitable consequence of a hypermasculine sporting culture (Waterhouse-Watson, 2013). This sentiment is then normalized through the tone and framing utilized by news media to convey reporting on these instances to the public (Henley, Miller, & Beazley, 1995). In early tweets on Broad's identification and sanction on social media, Reference accounts produced tweets that delivered sentiment-neutral or sympathetic representations of Broad and his sanction, as exemplified in the following tweets (identifying information has been redacted):

Richmond's Nathan Broad: “I'm embarrassed and ashamed.. I deserve to be punished.” Suspended for three matches re nude photo. @9NewsMelb

18 replies 15 retweets 20 likes

BREAKING: Nathan Broad takes “full responsibility” for Tigers nude photo scandal

3 replies 2 retweets 1 like

Each of these tweets, produced by a major broadcaster or journalist, legitimated Broad's sanction through passive or neutral tone or the inclusion of quotes referencing Broad's regret and shame. The diffusion of neutral and sympathetic responses to Broad throughout Reference responses to his sanction held the potential to reinforce the “narrative immunity” (Waterhouse-Watson, 2013, p. 5) of male athletes who engage in sexual misconduct.

However, as time progressed and the counterpublic narrative among Listeners continued to call out Broad and RFC, Reference account narratives of his actions began to shift. Tweets, again originating from news media accounts and journalists, began to echo the sentiment held by Listener accounts who took a critical and largely unsympathetic view of Broad and made frequent reference to the inadequacy of the sanction:

Shocked at the Twitter vitriol being directed at the woman in Nathan Broad's photo.. All from men. It's not a crime to pose for a picture.

37 replies 16 retweets 194 likes

COMMENT: A longer ban would have been appropriate for Nathan Broad


16 replies 9 retweets 29 likes

Tweets and news articles also began to appear that specifically referenced the public response to the incident:

There's been an outcry over a three-match suspension handed to Nathan Broad, at the centre of a topless photo scandal. @AyrtonWoolley #9News


9 News Melbourne, nightly at 6.00p.m.

6 replies 1 retweet 5 likes

Milivojevic and McGovern (2014) documented a similar pattern of news media acknowledging and endorsing social media sentiment in their study of the Jill Meagher case. Reporting that explicitly acknowledges an informal justice-seeking response to incidents of sexual assault represents a determination by news media that such responses are “newsworthy.” This ultimately culminated in a vast majority of Reference users reporting on the incident echoing the sentiment of Listeners:

Catherine Ordway (speaking about Nathan Broad): “Let's have him put his money where his mouth is and actually walk the talk. Go and work with some charities, go and show us that you do respect women.” #TheProjectTV

9 replies 10 retweets 34 likes

Stevie J 6 weeks for public drunkenness. Didak & Shaw last 6 games for lying re crash. M.Stokes 7 for drug charge. Nathan Broad deserved 4+

60 replies 36 retweets 296 likes

There was a clear, temporal progression in the sentiment shift of Reference accounts responding to the Broad incident over the three days that the story occupied headlines. This shift contrasted significantly with the approach of news media sentiment outlined in preexisting literature to similar incidents (Waterhouse-Watson, 2013). Given Reference accounts in this dataset were prominent broadcasting figures, this process exemplifies the shift in institutional agenda-setting first observed by Milivojevic and McGovern (2014). We suggest that the tweets by Reference accounts of the Broad incident were specifically influenced by social media outcry – a phenomenon that sees media institutions moving away from harmful discourses that minimize sexual harms committed by male athletes (Waterhouse-Watson, 2013).

These findings echo and support the hierarchized model of social media engagement discussed earlier in this chapter. The articulation of Reference accounts within social media networks, and their engagement with Listener subcommunities via Mediator accounts, provides a model of the reverse flow of sentiment enabled by social networking platforms (Sayre, Bode, Shah, Wilcox, & Shah, 2010). In the context of the Broad incident, this model articulates the intervention and disruption of sentiment-neutral discourses by social media users committed to expressing their discontent and frustration at Broad and the institutions that failed to adequately prosecute his behavior.


Studying phenomena such as TFV and IBSA requires innovative methods to attend to the complexities and nuances of justice in the digitized field. This pilot study has sought to bring the mechanics of the technology-enabling TFV and IBSA into focus by visualizing the structural patterns of behavior exhibited by users commenting about the Broad incident on Twitter. This study has illustrated how Twitter facilitated counterhegemonic discourses in relation to Broad's IBSA, and how these discourses disrupted and influenced news media sentiment that initially diminished the harms caused by IBSA. This has important implications for policy makers and practitioners responding to IBSA. It provides a substrate for understanding information diffusion and agenda-setting within the diffuse realm of social media structures, and how these structures impact public engagement with crime and criminality more widely.

The framework and findings discussed in this chapter may also prove helpful for other social media studies concerning responses to harm and crime on social media. The use of SNA is a relatively new and underutilized method within the social sciences (but see, Bright, 2015; Bright & Delaney, 2013; Bright, Greenhill, Ritter, & Morselli, 2015). Fig. 40.5 provides a representation of the ongoing interactions between differing hierarchies of users engaging with the Broad incident. We have highlighted the value of producing a structural representation of informal justice-seeking. This enabled the visualization of links between users, the generation of reverse flows of sentiment, and an analysis of how informal online justice-seeking is mediated by streams of incoming and outgoing information flows within a hierarchy of users.

Fig. 40.5. 
Social Media Spectatorship and Image-Based Sexual Abuse.

Fig. 40.5.

Social Media Spectatorship and Image-Based Sexual Abuse.

Given this was a pilot study, it has pointed to avenues for further inquiry on online engagement and IBSA, such as considering user engagement on another platform such as Facebook or Instagram. Further, the production of a larger SNA may provide further detail on the role of Mediator accounts within a wider network, and their specific position within the diffusion of information between Reference and Listener accounts. A further avenue for inquiry can be drawn from the fact both Broad and the woman he victimized are nonracialized, an important limitation when considering the sympathetic discourses observed in our results. SNA and ATA may prove useful for future studies examining specific media biases toward victims of TFV who are also members of marginalized communities. As social media evolves, so will its ability to enable digital sexual harms, and so we must consider the nature of information diffusion within the structure of online spaces. Methods such as SNA and ATA provide criminological scholars with tools to generate constructive accounts of the structure and flow of discourse surrounding incidents of IBSA and TFV. They offer the opportunity for tentative optimism on the nature of digital justice on social media platforms, and their role in disrupting and intervening in dominant narratives on sexual harm on the digital field.



The framing here is a deliberate choice by the authors to hold the perpetrator in sight and to account.


Print readers are encouraged to access the digital version of this paper, or to contact the authors for a digital copy, as figures are not designed to be interpreted in black and white.


Irrelevant tweets were bot tweets which aggregated “trending” topics, which provided neither sentiment nor news relevance.


Verified users indicate that the user is a legitimate account of public interest – those who may represent journalism, media, government, or other key interest areas.


Examples of tweets with negative coding include “Nathan broad is a total scumbag @AFL,” whereas neutral coding encompassed sentiment-neutral responses, i.e., “Today, Richmond's Nathan Broad received a 3 week suspension for distributing a nude photo of a woman without her consent.”


This ratio is the product of the limitations inherent to the scope of what was a small-scale pilot study. A larger study replicating these methods with an internationally recognized celebrity incident would provide greater engagement and thus a larger corpus of public sentiment for analysis.


This study received ethics approval through the University of Melbourne Arts HREC in 2018, application ID: 1851376.1.


One Reference account was excluded from analysis as it represented a broadcaster not consistently associated with AFL reporting.


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Technology-Facilitated Violence and Abuse: International Perspectives and Experiences
Section 1 TFVA Across a Spectrum of Behaviors
Chapter 1 Introduction
Chapter 2 Is it Actually Violence? Framing Technology-Facilitated Abuse as Violence
Chapter 3 “Not the Real World”: Exploring Experiences of Online Abuse, Digital Dualism, and Ontological Labor
Chapter 4 Polyvictimization in the Lives of North American Female University/College Students: The Contribution of Technology-Facilitated Abuse
Chapter 5 The Nature of Technology-Facilitated Violence and Abuse among Young Adults in Sub-Saharan Africa
Chapter 6 The Face of Technology-Facilitated Aggression in New Zealand: Exploring Adult Aggressors' Behaviors
Chapter 7 The Missing and Murdered Indigenous Women Crisis: Technological Dimensions
Chapter 8 Attending to Difference in Indigenous People's Experiences of Cyberbullying: Toward a Research Agenda
Section 2 Text-Based Harms
Chapter 9 Introduction
Chapter 10 “Feminism is Eating Itself”: Women's Experiences and Perceptions of Lateral Violence Online
Chapter 11 Claiming Victimhood: Victims of the “Transgender Agenda”
Chapter 12 Doxxing: A Scoping Review and Typology
Chapter 13 Creating the Other in Online Interaction: Othering Online Discourse Theory
Chapter 14 Text-Based (Sexual) Abuse and Online Violence Against Women: Toward Law Reform?
Section 3 Image-Based Harms
Chapter 15 Introduction
Chapter 16 Violence Trending: How Socially Transmitted Content of Police Misconduct Impacts Reactions toward Police Among American Youth
Chapter 17 Just Fantasy? Online Pornography's Contribution to Experiences of Harm
Chapter 18 Intimate Image Dissemination and Consent in a Digital Age: Perspectives from the Front Line
Section 4 Dating Applications
Chapter 19 Introduction
Chapter 20 Understanding Experiences of Sexual Harms Facilitated through Dating and Hook Up Apps among Women and Girls
Chapter 21 “That's Straight-Up Rape Culture”: Manifestations of Rape Culture on Grindr
Chapter 22 Navigating Privacy on Gay-Oriented Mobile Dating Applications
Section 5 Intimate Partner Violence and Digital Coercive Control
Chapter 23 Introduction
Chapter 24 Digital Coercive Control and Spatiality: Rural, Regional, and Remote Women's Experience
Chapter 25 Technology-Facilitated Violence Against Women in Singapore: Key Considerations
Chapter 26 Technology as Both a Facilitator of and Response to Youth Intimate Partner Violence: Perspectives from Advocates in the Global-South
Chapter 27 Technology-Facilitated Domestic Abuse and Culturally and Linguistically Diverse Women in Victoria, Australia
Section 6 Legal Responses
Chapter 28 Introduction
Chapter 29 Human Rights, Privacy Rights, and Technology-Facilitated Violence
Chapter 30 Combating Cyber Violence Against Women and Girls: An Overview of the Legislative and Policy Reforms in the Arab Region
Chapter 31 Image-Based Sexual Abuse: A Comparative Analysis of Criminal Law Approaches in Scotland and Malawi
Chapter 32 Revenge Pornography and Rape Culture in Canada's Nonconsensual Distribution Case Law
Chapter 33 Reasonable Expectations of Privacy in an Era of Drones and Deepfakes: Expanding the Supreme Court of Canada's Decision in R v Jarvis
Chapter 34 Doxing and the Challenge to Legal Regulation: When Personal Data Become a Weapon
Chapter 35 The Potential of Centralized and Statutorily Empowered Bodies to Advance a Survivor-Centered Approach to Technology-Facilitated Violence Against Women
Section 7 Responses Beyond Law
Chapter 36 Introduction
Chapter 37 Technology-Facilitated Violence Against Women and Girls in Public and Private Spheres: Moving from Enemy to Ally
Chapter 38 As Technology Evolves, so Does Domestic Violence: Modern-Day Tech Abuse and Possible Solutions
Chapter 39 Threat Modeling Intimate Partner Violence: Tech Abuse as a Cybersecurity Challenge in the Internet of Things
Chapter 40 Justice on the Digitized Field: Analyzing Online Responses to Technology-Facilitated Informal Justice through Social Network Analysis
Chapter 41 Bystander Apathy and Intervention in the Era of Social Media
Chapter 42 “I Need You All to Understand How Pervasive This Issue Is”: User Efforts to Regulate Child Sexual Offending on Social Media
Chapter 43 Governing Image-Based Sexual Abuse: Digital Platform Policies, Tools, and Practices
Chapter 44 Calling All Stakeholders: An Intersectoral Dialogue about Collaborating to End Tech-Facilitated Violence and Abuse
Chapter 45 Pandemics and Systemic Discrimination: Technology-Facilitated Violence and Abuse in an Era of COVID-19 and Antiracist Protest