Digital Archives and Unexpected Crossings: A Data Feminist Approach to Transnational Feminist Media Studies and Social Media Activism

Abstract

The urgency and complexity of contemporary social justice issues facing the world today mean that activists, scholars, and storytellers need a readily available compendium of cutting-edge scholarship on media and social justice. This handbook represents the collective wisdom of more than 40 leading voices across positionalities and perspectives, geographies and generations, meta-theories and methods, and issues and identities. Each of the 32 chapters presents a state-of-the-art systematic overview of a brief history, key concepts, contemporary debates and dialogues, and future directions. The book begins with introductory remarks on perspectives, positionalities, and paradigms. The section on approaches and analytical frameworks examines classic and contemporary media theories related to social justice such as political economy, critical cultural studies, reception studies, and framing analyses. The next section on methods and meaning-making reviews methodological tools such as quantitative criticalism, media ethnography, and critical discourse analysis for media justice researchers. These theories and methods are then applied to specific intersectional identities, contemporary social issues, and communities worldwide in the next section: “Resistance and Revisioning. The book concludes with reflections on resistances, reckoning, and reparative justice.

Full text

The Oxford Handbook of Media and Social Justice
Srividya Ramasubramanian (ed.), Omotayo O. Banjo (ed.)
https://doi.org/10.1093/oxfordhb/9780197744345.001.0001
Published: 2024 Online ISBN: 9780197744376 Print ISBN: 9780197744345
CH AP TE R
https://doi.org/10.1093/oxfordhb/9780197744345.013.16 Pages 141–150
Published: 19 September 2024
Abstract
Keywords: #EndDiscriminationAgainstHijab, digital archives, small social data, social media activism,
context collapse
Subject: Social Psychology, Psychology
Series: Oxford Library of Psychology
Collection: Oxford Handbooks Online
16 Digital Archives and Unexpected Crossings: A Data
Feminist Approach to Transnational Feminist Media Studies
and Social Media Activism 
Ololade Faniyi,Radhika Gajjala
This chapter explores the hashtag #EndDiscriminationAgainstHijab within a larger context of digital
archives as it connects to transnational hijab struggles. Adopting a data feminist approach, the chapter
presents an exploration of Twitter data related to a small, situated part of the larger conversation
around the #hijab. Through computational analysis and close feminist reading of tweet clusters, the
examination focuses on the contextual implications in Nigeria and reveals instances of context
collapse. It examines how users intentionally forge links between distinct hijab struggles in Iran and
Nigeria, as well as draw connections between Amada Firdaus’ hijabi resistance and Rosa Parks’
activism. Emphasizing the signicance of networked conversations on Twitter, the ndings highlight
powerful connections that transcend geopolitical borders. By showcasing the navigation and
contextual interpretation of these tweet interactions, the chapter aims to highlight the importance of
engaging with context, power structures, and agency in social media activism for transnational
feminist media studies scholars.
If a woman faced imprisonment, exclusion from an educational institution, or even loss of life due to her
choice of wearing or not wearing hijab, many of us would rst hear about it through social media. We would
then embark on an online exploration, clicking on numerous related links in search of a clearer
understanding. These links would often lead us to platforms such as Instagram, Twitter, or Facebook. We
would scrutinize the information, questioning if it could be misinformation or propaganda from an
unknown source. To verify the authenticity, we would turn to legacy media websites, reminiscing about the
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

material experience of holding a newspaper as we placed our trust in websites displaying familiar logos.
Convinced of the event’s occurrence, we would return to Instagram, Twitter, or Facebook to dig further into
threads and comments. As we multitasked or procrastinated on work emails, we would venture further
through hashtags and retweet links, encountering conicting opinions, trolls, and advertisers capitalizing
on the trending hashtag. We would discover distinct clusters of interactions within niche communities, each
with their own perspectives on the issue. Immersed in our lter bubbles or entering spaces of intense
contention, we would experience unexpected encounters. As researchers, we would eventually set aside our
cup of coee and document our ndings, scrolling through our screens as we begin to consider the
implications of what we witnessed unfolding in real time across transnational digital publics.
In this case, as communications researchers interested in how events from the Global South become visible
through algorithmic publics and how counterpublics are being formed by users, members of our research
team—Research Lab for Situated Data Analytics, Digital Humanities, Digital Archiving and Data Feminism
—began a urry of email exchanges, text messages, and WhatsApp conversations. With each of us
attempting to make sense of what was happening, we are implicitly informed by our own sociocultural and
generational backgrounds as many of us had personal experiences in the geographical locations being
“tweeted” and “instagrammed” about. Several of the clusters of communication we encountered on social
media connect in the big social media data space to create a visual battleeld of contestations and debates.
What sorts of discursive contestations and nuances emerge around the “hijab” in such mediated
environments? Employing our preferred methods of data collection, some of us frantically captured
screenshots from Instagram, while others hastily set up data visualization software on their laptops to
locate and download relevant messages using specic keywords and hashtags. Meanwhile, a few among us
turned to the Twitter application programming interface (API) downloader to retrieve historical data, driven
by a curiosity to understand when this news had originally burst forth on the platform.
In our quest to understand what was happening—how the stories were being told, why they were being told,
and the practices made possible or impossible because of the features of each social media platform—we
became a haphazard group of accidental hashtag archivists. As highlighted by Dencik (2019), the
performative power of data plays a crucial role in explaining the profound impact of datacation on the
transformation of both our social fabric and academic culture. This process of archiving social media data
requires curating and contextualizing what emerges in digital publics. As Conley (2021) argues,
“communication technologies transform, interfaces disappear, meaning constructed through social media
use changes” (p. 755). These accidental archives are derived and mapped through situated human
(researcher) recognition, where smaller sets of data begin to make sense through contextual
understandings and research oine. However, nestled within big social data, they also become “uncertain
archives,” characterized by ambiguity, errors, and vulnerabilities (Thylstrup et al., 2021). Therefore, beyond
the descriptive part of Twitter text lies a critical data gap that holds contextual signicance.
p. 142
Unveiling Nuances Through Combining Quantitative and Qualitative
Approaches in Social Media Data Analysis
Often, the data collected in response to trending hashtags contain very few actual texts, and the signicance
of these data sets arise from the number of retweets they receive. Thus, the algorithmic infrastructure that
makes visible a particular topic via select hashtags operates on the basis of quantication. The greater the
number of retweets and likes, the higher the likelihood that the topic will reach a broader audience within
the social media platform. Indeed, other factors inuence content visibility on each platform, such as a
user’s follower count, the accounts they follow, or their verication status as a “blue tick” user. However,
the text itself is not always highly nuanced, so an interpretive approach focused only on examining the text
may not produce an understanding of what is happening on the platform.
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

We can observe the existence of polarized views on various topics, identify instances of right-wing
propaganda, and recognize the contribution of social media platform content to the spread of hatred. We
might also note that protestors are mobilizing the use of social media. However, the textual content itself is
not thick enough to provide the context of detail without the researcher doing additional research that goes
beyond the platform being examined. Likewise, examining the data purely through the quantitative analytic
tools available for scraping masses of big data tells us very little. For instance, when we scraped the data on
#hijab for 60 days using Netlytic.org or spent a few hours over several days using the open-source software
Gephi, the statistical features mainly gave us a descriptive overview of the number of connected clusters of
users and “betweenness centrality”—the inuence of users in propagating hashtags or conversations
across clusters. These details make no sense unless we look closely at the textual data.
Adopting either a qualitative textual approach or a purely quantitative approach, while providing a glimpse
into the descriptive aspects of the data, failed to yield a nuanced understanding. However, combining these
analytical approaches with background research and contextual understanding of the larger events that
prompted the social media posts proved more productive. We began to see how social media inuencers
contributed to creating visibility for particular kinds of content through specic practices aimed at jostling
the platform algorithms to enhance visibility. Regardless of what side of the debate the person tweeting is
on, they adopt the same practices to enhance their content’s visibility. These practices are shaped by a
marketing logic because social media platforms (e.g., Twitter and Meta Platforms) are situated in this logic
(Burgess & Bruns, 2015).
Our contribution in this chapter, therefore, is to point to the interesting practices within Twitter that yield
unexpected or unique information and transnational visibility for local issues—accidental archives
perhaps—connecting through some highly visible hashtags. Approaching what we see online as enmeshed
in everyday praxis while also structured through algorithmic and oine hierarchies of governmentality and
access to technology, we argue that to understand the implications of the multiplicity of crisscrossing
communicative exchanges online, we must take both a macro and a micro look at the data sets. As low-
resourced social science and humanities researchers in a mid-level university trying to do this work, our
team comprised a small group of graduate students and a faculty member adopting a self-styled “do-it-
yourself” approach. We negotiated access to computational software and computer space, among other
things, which compelled us to work with smaller subsets of the extensive data available through our
academic researcher and developer access to Twitter API tools. Our goal was to try to get a deep look at
sections of the data, leveraging privileged sociocultural context and praxis of technology use. As highlighted
by Ruppert et al. (2017), the “emergence and transformation of professional practices such as data science,
data journalism … and data analysis” (p. 1) are intricately linked to the reconguration of power dynamics
and knowledge production in the accumulation of public and private data.
p. 143
1
Therefore, we started our spontaneous archiving of Twitter data around the hashtag “hijab” following two
events: the ban on hijabs in a school in Karnataka, India, and the killing of an Iranian woman, Mahsa Amini,
by all accounts, over the “incorrect” wearing of the hijab in Iran. Although this chapter represents part of a
larger investigation into the hashtagication of “hijab” that we started in 2022, it deviates from examining
those specic events. During the data analysis process, one of our collaborators (the rst author of this
chapter), a young Nigerian woman and feminist activist currently pursuing a doctorate degree in Atlanta,
Georgia, after obtaining her Master of Arts degree in northwest Ohio, identied tweet clusters that
resonated with her sociocultural background. As a result, this chapter discusses these select data clusters
around the Nigerian context, while other clusters are being examined and written about by co-authors in
other essays (Gajjala et al., 2024). In the following sections, we describe the Nigerian context, discuss the
methods employed, and present the emerging themes from analyzing the data and practices of relevant
Twitter users.
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

The Nigerian Context
In December 2017, a law school graduate, Amasa Firdaus, was denied her call to bar, a legal ceremony that
signies a lawyer’s qualications to represent another in court, because she was wearing a hijab beneath
her lawyer wig—a headpiece made from horsehair worn by barristers in Nigeria and other Commonwealth
countries during formal events and court proceedings. This sparked a series of conversations in digital
“anxious” publics and traditional media about the right of Muslim women lawyers to choose and express
their religious values, including the right to wear their hijab to their call to bar ceremony. In Nigeria, social
ideologies encompass a diverse combination of Africanist/traditional, Eurocentric, and Arabic legacies and
inuences that vary across dierent regions, and the country reects a normative framework shaped by an
interplay of religion, culture, and colonial ethics. The 2015 report from the Pew Research Center reveals that
50% of Nigerians are Muslim, 48.1% are Christians of varying denominations, and 1.9% are either
traditional African religious or unspecied (Hackett et al., 2015). #EndDiscriminationAgainstHijab soon
emerged in response to Firdaus’ denial to the call to bar, causing a series of religion-centered conversations
in which Muslim men and women and others with non-Muslim beliefs debated on Firdaus’ resistance
despite how much she had to lose.
Firdaus was eventually called to bar in 2018 after the Body of Benchers passed a resolution that stopped the
discrimination of hijabi lawyers and approved their wearing of the hijab at the call to the bar ceremony.
Since 2018, every call to bar has led to the mention of Firdaus’ name on Nigerian Twitter, with new hijabi
lawyers thanking her for her victorious struggle against their discrimination. Here, we explore not just how
this resistance played out in digital publics in December 2017 but also the context collapse that emerged as
users made connections to Iran and the resilience of Rosa Parks. Although this is a relatively small data set
within the multitude of transmissions in big online data sets, what makes this Nigerian hijabi struggle
important for our feminist intersectional small data research is how users from Global South contexts
engage hashtags to produce visibility for their protests and connect these messages with clusters online,
despite geographical location. In addition, they also connect their activism to crossings beyond their
context as stories that give them strength and educated hope for an equitable future.
p. 144
Method: Analyzing Digital Archives with a Data Feminist Approach
Approaching the comparatively small sets of collected archives as feminist researchers required us to
attempt to unravel contextual specicities in layers. This process also required us to examine practices of
Twitter use as material practices within the “habitus” (Bourdieu, 1995) that is Twitter. Rather than treating
the social media platform as a at surface of discursive texts, images, and shared links or the algorithmic
infrastructure as a at hierarchy implicitly and intentionally coded, we center our experience working to
retool computational tools for social media research from a critical humanities lens (Gajjala et al., 2024). We
rst discuss the human collaboration process and then describe how we worked with computational tools to
examine “small social data.” Finally, we use one example from a recent research project to discuss how we
worked together to arrive at evidence-based yet self-reective and critically engaged conclusions.
For this project, we started with two sets of spontaneously collected data engaging the aordances of
Python scripts in Google Colab, Netlytic, DiscoverText, Gephi, and ATLAS.ti to scrape Twitter data. We
collected data using the keyword and hashtag “hijab’ in February 2022, when we heard of the hijab ban in
Karnataka, India, and later in September 2022, when Mahsa Amini was killed in Iran. The data, gathered
through our Twitter API access, revealed to us the dynamic, shifting nature of content in Twitter publics.
While examining these sets of spontaneously collected data in 2022, we noted dierent contexts in which
the keyword or hashtag “hijab” was deployed. We also noted that a strategy for ensuring visibility for
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

dierent contexts was to piggyback on already existing highly visible hashtags from other contexts, making
cultural crossings shaped by ideologies that manifest in various encounters and use of digital networks by
users. As established, this chapter, taken from a larger investigation around the hashtagication of “hijab”
in 2022, examines specically the case highlighted from Nigeria.
As mentioned previously, our methods are mixed as we adopt close feminist reading and data analytics tools
for networked data scraping and visualization. As data feminist or feminist digital humanities scholars, we
acknowledge the digital labor of activists engaging with hashtags to produce visibility for their resistance
against state and non-state oppressors (Faniyi et al., 2023). We must, however, note here that our approach
does not credit the mediatization of the work of activists to the digital networks without acknowledging the
oine groundwork or cultural specicity that made them feminist/political subjects in the rst place. In
fact, our work is rooted in an awareness of the ways in which social media platforms, which have been
rightfully criticized for operating on racist and extractive logic (Benjamin, 2019; Noble, 2018), continue
to privilege certain dominant voices while depending on the emotional labor and community management
of activists and women from marginalized backgrounds who might nd the “freedom” to express their
feelings on these platforms inspiring.
p. 145
However, we nonetheless acknowledge that social networks and data collecting sites such as Twitter give us
access to a material archive of the work done and curated by activists’ agential capabilities. As Florini (2019)
argues, Twitter “commonly serves as a content aggregator and bridge between multiple platforms” (p. 70).
Therefore, as the oine activist eort feeds into the digital production of visibility, we use computational
tools to lter and visualize these data. With the “bigness” of data typical of digital networks, our approach
centers small parts of this larger data by amplifying resistance from whisper networks and counterpublics
that might often seem minute in comparison to other big data sets online but are no less subversive in
exemplifying intentional or unlikely activists pushing against the oppressive status quo. As a team, we have
explored these manifestations across several Global South contexts, including India, Nigeria, Iran, and
Afghanistan, in interrogating hashtag activisms such as #womenofshaheenbagh, #sayhernamennigeria,
and #hijab. Our approach to undertaking feminist intersectional small data research engages big data tools
in our attempt to intentionally center voices from the margins in context. For instance, the hashtag
movement #sayhernamenigeria had a frequency of 74,059 mentions after one year since its emergence in
April 2019, compared to the millions of hashtags in larger transnational movements. However, what small
data sets such as #sayhernamenigeria and big data sets such as #sayhername and #BLM reect across
contexts is citizen-led resistance against police brutality with critical intersectional nuances.
By pushing against the grain of generalization or attening typical with work on big data sets online, our
approach prioritizes activists as co-authors of the discourses they create in line with the precedent of
scholars such as D’Ignazio and Klein (2020) and Jackson et al. (2020). Our work centers the principles of
data feminism, as coined by D’Ignazio and Klein, as “a way of thinking about data, both their uses and their
limits, that is informed by direct experience, by a commitment to action, and by intersectional feminist
thought” (p. 9). In this way, our data feminist perspective refers to our application of feminist intersectional
principles to our mixed methods quantitative and close feminist reading approaches, as well as, more often
than not, in-depth interviews that place human, contextual, and historical specicity in otherwise
taxonomical machine-to-machine communication.
Members of our team have varied experiences working in data analytics and feminist activism; some of us
have been imbricated as participants/observers in the workings of activist communities online. Before the
formal construction of digital humanities as a eld, our work had established us as accidental hashtag
archivists who curated the repertoire and archive of feminists/women in overt or subtle protest against the
matrices of oppression, countering the “big”-ness of computational data with careful multiple locationally
situated analysis.
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

In this chapter, our process details how our work examining digital archives on Muslim women’s resistance
against the state and oppressive systems established us as (accidental) hashtag archivists creating contexts
from the evidence of their activism. Because a fraction of our data is not historical—that is, we did not
collect it live but, rather, after a period of active aective transmissions online—we used a Python script to
collect data on the peak period of #EndDsicriminationAgainstHijab from December 14, 2017, to December
16, 2017, revealing that the hashtag was used 5,977 times within that period. Our Python script ran once for
15 minutes, and we got the data into formats as a .json le and node and edges data in .csv. We converted the
.json le for reading convenience into .csv, and these data relayed users’ tweet text, ids, locations,
mentions, and accompanying image URLs, among others. Despite this ease of access oered by our
computational tools, the human agency and feminist practices still came to the fore as we worked
through the data manually to lter deleted tweets or tweets from users whose identities must be protected
from unwarranted hypervisibility.
p. 146
While we acknowledge the threats to user privacy and security that can result from unethical use of Twitter
data, we situate our research on the knowledge that just as this access and data can be extractive and
exploitative, it nonetheless oers a solution to inequalities and oppression. Data is power, and even more
so, visibility and archiving are important for activism and resistance. Our Python script networked this
hashtag into nodes and edges—that is, the people in the network and the connections between them. We
imported these into Gephi, the network visualization tool that allowed us to closely read smaller chunks of
data and lter as needed. We referred to our converted .csv Twitter data set le as we looked through our
previewed visualizations to locate original tweet text and connections between users and their mentions.
Our close feminist intersectional reading was thus the basis of our analysis as we interpreted from the
information revealed by the nodes and clusters what eld of possibilities and aordances digital networks
oered voices from Nigeria and the Global South.
#EndDiscriminationAgainstHijab: Deliberate Connections Between
Historical Contexts of Muslim Womenʼs Activism
Our attention was drawn to context collapse in this data set, exemplied by the blurring of distinct contexts
when various sociopolitical and cultural backgrounds collide in online conversations. This phenomenon,
potentially leading to misunderstandings and oversimplication, became evident through a specic tweet
interaction involving users @hauwa_ojeifo, @adlexy, and @oduolates (Figure 16.1). By examining the
deliberate connections made between dierent historical contexts of Muslim women’s activism, we
argue for the crucial understanding of specic sociopolitical nuances within which struggles for agency and
freedom unfold, while debasing universalizing tendencies that overlook contextual factors in discussions on
Muslim women’s agency.
p. 147
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

Figure 16.1 Context collapse blurring contexts and meanings of Muslim women.
The original tweet by user @hauwa_ojeifo had praised the Amasa Firdaus in appreciation of the several
hijabi lawyers called to bar in 2022. User @adlexy responded by connecting to the ongoing Iranian
revolution and hashtag activism #mahsamini. Mahsa Amini, a 22-year-old Iranian woman, was detained on
September 13, 2022, because she was not wearing her hijab properly. She later died, reportedly at the hands
of Iran’s religious morality police. Her death provoked one of the largest demonstrations in Iran since 2009,
with female protesters cutting their hair or removing their hijabs publicly as an act of deance of Iranian
regulation of women’s bodies and appearance. It also reopened discussions about the hijab as a choice and
the regulation of (Muslim) women’s attire. Drawing from the insights of scholars such as Abu-Lughod
(2013), Mahmood (2005), and Razack (2008), user @adlexy’s insinuation that hijabi lawyers in Nigeria
needed help and saving due to the struggle against the hijab in Iran directly reects the Orientalist
discourses prevalent in Western perspectives, which portray veiled Muslim women as victims in need of
rescue, solely highlighting religion while attening the mutually occurring poverty, colonial violence, and
political authoritarianism. Abu-Lughod’s work, particularly her book Do Muslim Women Need Saving?,
challenges such Western assumptions and vocabulary and calls for a critical examination of power dynamics
aecting Muslim women’s lives. Mahmood’s book, Politics of Piety, also emphasizes veiled Muslim women’s
moral agency and subjectivity, as she questioned the Western liberal portrayal of veiled women as victims.
Just as Razack’s Casting Out explores how the construction of veiled Muslim women as threats in the context
of national security reinforces colonial power structures.
In response to @adlexy’s insinuation, user @oduolates asserts that the situations in Iran and Nigeria
represent opposite instances of women ghting for their right to choose. This tweet aligns with these
critical arguments highlighting the importance of understanding the diverse contexts, power dynamics, and
agency within hijab struggles. In Iran, the hijab is enforced by its government and morality police, but in
Nigeria, it is a choice, and Muslim women lawyers are defending their choice to wear it to their call to bar,
amidst the tensions and complexities of representation. On the one hand, the image of the female lawyer
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

would typically spark conversations on the need for empowerment and policies that allow women to pursue
careers just like men. On the other hand, this pride in the female lawyers called to bar that connects
strangers on the internet is disrupted by the symbiotic interactions of Islamophobia and radicalization
(Abbas, 2019) that, counter to the celebration of women’s agency, replicate the discrimination of Muslim
hijabi lawyers.
We used Gephi to visualize the #EndDiscriminationAgainstHijab data set in a network graph, which, based
on our assigned ltering and statistics, revealed the users and keywords with the highest degrees. The graph
shown in Figure 16.2 depicts a cluster of nodes representing Twitter users, hashtags, keywords, and other
metadata with high centralities in the #EndDiscriminationAgainstHijab network. The nodes are connected
by edges indicating the frequency and strength of interactions between the metadata. The nodes and edges
have distinct colors showing the dierent clusters of users online in conversation with one another.
The phenomenon of context collapse often manifests in nonlinear ways, either through users’ deliberate
connections or through the interventions of other users engaging the tweet. Figure 16.3 shows how
@ogundamisi connects Firdaus’ resistance to Rosa Parks, an American civil rights activist remembered for
the Montgomery bus boycott after she refused to give up her seat on a bus in Montgomery, Alabama, in
favor of a White passenger. In response, another user asks, “What does Rosa Park have to do with this?” and
@ogundamisi responds, “a lot, defying the norm, challenging the norm so society can reect and adjust.
Got it now,” accompanying this tweet with an eye-roll gif. In many ways, this tweet connects to a deliberate
legacy of activism similar to Firdaus. Furthermore, this example of context collapse highlights the unique
information yielding from highly visible networks and showcases an unprecedented situation of Firdaus
among a legacy of activists who courageously defend their dignity and right to freedom and choice, even
when these are from distinct historical contexts.
p. 148
Figure 16.2 Visualization of the #enddiscriminationagainsthijab network between December 14 and 16, 2017, generated
through Gephi. Nodes are sized by degree—that is, the number of times retweeted and mentioned.
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

Conclusion
In this chapter, we explored #EndDiscriminationAgainstHijab by extracting it from the broader data that
form digital archives on hijab resistance. We noted how our journey through the archives led us to this
unexpected local cluster of meaning-making amid the larger transnational debates around the hijab. We
highlighted how our data feminist approach and close attention to small clusters of data bring out nuances
that need to be engaged by transnational feminist media studies scholars. This chapter draws on our
spontaneous archiving of Twitter data (since 2022) on the #hijab with a close look at the contextual
implications in Nigeria that we accidentally encountered because we did not enter the platform with
predetermined expectations of what we would nd. Examining tweet clusters that connect with the
sociopolitical implications in Nigeria, we highlighted events that sparked a context collapse as Twitter users
deliberately connected ideologically distinct hijab struggles in Iran and Nigeria, and further connected
Amada Firdaus’ resistance to Rosa Parks’ activism. However, although we have curated situated sections of
the data, we make no claims that we have a general overarching understanding of all contexts in which this
hashtag was deployed.
p. 149
Figure 16.3 @ogundamisinario of context collapse emerging #Enddiscriminationagainsthijab with Rosa Parksʼ activism.
As Dencik (2019) argues, there is an ongoing challenge of comprehending how diverse actors utilize and are
inuenced by data in their understanding and actions regarding social and political issues. For instance, in
the case of Iran, not all activists and social media inuencers agree on the issue of hijab as choice, whereas
in the case of the Indian context, the hijab issue takes on other complex and contextual directions. Overall,
we emphasize the critical importance and interesting practices within networked conversations on Twitter
that yield unexpected or unique information and transnational visibility for local issues, linking via highly
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

visible hashtags and fostering powerful crossings that transcend geopolitical borders. With this chapter, we
aim to provide readers with a deeper understanding of the complexities surrounding the tweet
interactions, urging critical thinking about context, power structures, and agency in the context of
transnational feminist media studies and social media activism.
p. 150
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

References
Abbas, T. (2019). Islamophobia and radicalisation: A vicious cycle. Oxford University Press.
Google Scholar Google Preview WorldCat COPAC
Abu-Lughod, L. (2013). Do Muslim women need saving? Harvard University Press. https://www.jstor.org/stable/j.ctt6wpmnc
Google Scholar Google Preview WorldCat COPAC
Benjamin, R. (2019). Race aer technology: Abolitionist tools for the New Jim Code. Wiley.
Google Scholar Google Preview WorldCat COPAC
Bourdieu, P. (1995). Structures, habitus, practices. In J. Faubion (Ed.), Rethinking the subject (pp. 31–45). Routledge.
Google Scholar Google Preview WorldCat COPAC
Burgess, J., & Bruns, A. (2015). Easy data, hard data: The politics and pragmatics of Twitter research aer the computational turn.
In G. Langlois, J. Redden, & G. Elmer (Eds.), Compromised data: From social media to big data (pp. 93–111). Bloomsbury.
Google Scholar Google Preview WorldCat COPAC
Dencik, L. (2019). Situating practices in datafication: From above and below. In H. Stephansen & E. Treré (Eds.), Citizen media and
practice: Currents, connections, challenges (pp. 243–255). Routledge.
Google Scholar Google Preview WorldCat COPAC
DʼIgnazio, C., & Klein, L. F. (2020). Data feminism. MIT Press.
Google Scholar Google Preview WorldCat COPAC
Faniyi, O., Nduka-Nwosu, A., & Gajjala, R. (2023). #SayHerNameNigeria: Nigerian feminists resist police sexual violence on
womenʼs bodies. In B. Wiens, M. MacArthur, S. MacDonald, & M. Radzikowska (Eds.), Stories of feminist protest and resistance:
Digital performative assemblies (pp. 51–66). Lexington Press.
Google Scholar Google Preview WorldCat COPAC
Florini, S. (2019). Beyond hashtags: Racial politics and Black digital networks. New York University Press.
Google Scholar Google Preview WorldCat COPAC
Gajjala, R., Faniyi, O., Rahut, D., Edwards, E., & Ford, S. (2024). Get the hammer out! Breaking computational tools for feminist,
intersectional “small data” research. Journal of Digital Social Research, 6(2), 9–26.
Google Scholar WorldCat
Hackett, C., Connor, P., Stonawski, M., Skirbekk, V., Potančoková, M., & Abel, G. (2015). The future of world religions: Population
growth projections, 2010-2050. Pew Research Center.
Google Scholar Google Preview WorldCat COPAC
Jackson, S. J., Bailey, M., & Welles, B. F. (2020). #HashtagActivism: Networks of race and gender justice. MIT Press.
Google Scholar Google Preview WorldCat COPAC
Mahmood, S. (2005). Politics of piety: The Islamic revival and the feminist subject. Princeton University Press.
Google Scholar Google Preview WorldCat COPAC
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press.
Google Scholar Google Preview WorldCat COPAC
Razack, S. H. (2008). Casting out: The eviction of Muslims from Western law and politics. University of Toronto Press.
https://www.jstor.org/stable/10.3138/9781442687554
Google Scholar Google Preview WorldCat COPAC
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024

Notes
Ruppert, E., Isin, E., & Bigo, D. (2017). Data politics. Big Data & Society, 4(2). https://doi.org/10.1177/2053951717717749
Google Scholar WorldCat
Thylstrup, N. B., Agostinho, D., Ring, A., DʼIgnazio, C., & Veel, K. (2021). Uncertain archives: Critical keywords for big data. MIT
Press.
Google Scholar Google Preview WorldCat COPAC
Since July 2023, the Twitter academic developer account and API tools has been restricted and monetized, as the
platform, under its new leadership became X. Our engagement in this chapter predates the Elon X takeover, so we stick to
the description that is faithful to that context.
1
Downloaded from https://academic.oup.com/edited-volume/58202/chapter/482139142 by OUP-Reference Gratis Access user on 04 October 2024