Journal of Digital Social Research

Special Issue on Methods in Visual Politics and Protest

Suay Melisa Özkula — 2024-05-24

This special issue forms the second part of a double issue on methods in visual politics and protest. It draws together five articles that provide new pathways for deconstructing visual political narratives and offers reflexive and nuanced accounts for researching visual data and information shared on social media platforms (here: TikTok, Instagram, Twitter/X, Facebook). They do so through the application of feminist mixed methods (femmix), cross-platform analysis, and context-aware, comparative, and triangulated approaches. Taken together, the double issue offers a substantive compendium of articles exploring the latest methodological developments in visual politics and protest.

Get the hammer out!

Radhika Gajjala — 2024-05-24

This paper focuses on revealing how the interplay between algorithmic interactions and the intuitive ways humans navigate digital environments can be researched through a multi-method approach to collecting and critically examining data from online platforms. We use a case study that looks at the role that social media engagement by transnational activists, local activists and celebrities played in amplifying an offline protest by group of women in India. Grounded in a critical feminist perspective, this paper uses multiple methods to demonstrate how the amplification of local protesters work through an interplay of human action and platform algorithmics. We conduct an algorithmic ethnography involving the examination of computational systems shaping online interactions. We examine the digital emergence and recognition of the women of Shaheen Bagh as subaltern political agents/subjects. Understanding of the interplay between online and offline visibility and strategic planning is highlighted. We conduct close readings of small data clusters that emerge within big data networks. We challenge the overreliance on big data methodologies and the fetishization of in-person ethnography (Bishop 2018) over digital ethnography.

Dwelling as Method

Brianna Wiens — 2024-05-24

This article proposes and delineates “digital dwelling” as one method of grappling with a central methodological challenge that we, as feminist researchers, face of how researchers might account for the multiple entanglements of affect, history, culture, politics, and resistance within feminist digital media artifacts. Using our method of digital dwelling, we analyze three sets of carousel posts on Instagram from three different accounts: Intersectional Environmentalist Collective, For the Wild, and Richa Kaul Padte. We explore how the inter, para, and meta-textual arguments curated through these carousel posts change the ways audiences relate to one another and to the current political moment, and how audiences, including individual researchers, are situated in affective and embodied ways within the research scene. By demarcating small, embodied data curation as a key space of method and analysis, we suggest that the personal relationships we develop in community as researchers with located acts of transgression, like these posts, are significant to consider more fully through their emergent intertextualities, especially for those invested in contemporary social media, protest, and visual cultures.

Researching visual protest and politics with “extra-hard” data

Suay Melisa Özkula — 2024-05-24

A range of scholars have criticised scholarly tendencies to focus on “easy” data such as provided by the low-hanging fruit of Twitter hashtag networks (Burgess & Bruns, 2015; Hargittai, 2020; Tromble, 2021). As a result, digital social research has been said to create a glut of studies that favour particular platforms, data forms, and networking dynamics, choices that may create ‘digital bias’ (Marres, 2017). These issues are particularly significant in visual data as the implicit nature of visuality means that platform spaces, text, and networked uses of visuals contribute to how visuals are interpreted in digital environments. In response to this issue, we present and critically reflect on new potentialities in software-based visual research on protest and politics, including: (1) rich cross-project comparisons; (2) complementing platform data with on-the-ground engagement, and (3) quali-quanti visual methods. These allow for rich data journeys through multi-modality, hybridity, comprehensive data curation, reiterative image data collection and interpretation, and the inclusion of contextual reflections in focused visual research, elements that provide meaning, texture, and context (= extra-hard data). We argue that visual digital methods consequently have the potential to provide nuanced, robust, and versatile analysis of visual data, if not necessitate these in a post-API age in which easy data access is no longer a given.

Understanding climate-related visual storytelling on TikTok

Jing Zeng — 2024-05-24

This cross-cultural study investigates the prevalence and impact of climate-related campaigns on TikTok, with a specific focus on climate-related visual storytelling in Indonesia, Japan, Pakistan, the Philippines, Thailand, the United Kingdom, and the United States. Computational methods are employed in the study to analyse a dataset of 7,564 videos, providing insights into prominent visual characteristics and regional variations. The findings underline the significance of cultural and political contexts in shaping climate storytelling on TikTok. Furthermore, this research explores the potential of computational visual data analysis in studying climate communication, demonstrating the integration of computer vision and topic modelling to examine visual styles and communicative functions in TikTok’s climate storytelling. The study enhances our understanding of climate communication on digital platforms and emphasizes the value of leveraging computational methods to gain meaningful cross-cultural insights into visual storytelling in the context of climate change.

Exploring leadership on Instagram

Michele Martini — 2024-05-24

Online visual communication is becoming an established and central component of citizens’ everyday life. User activity on large-scale platforms, such as Instagram, can be mapped by tracing the rise and fall of communities of practice that share different visual languages, aesthetic values and forms of leadership. Accordingly, the present study proposes an analytical model for the identification, measurement, and categorization of leadership on visual-based social networks, by asking: how does the digital performance of leaders on Instagram construct different forms of leadership? To answer this question, the Leadership Visual Performance Model (LVPM) will be presented as a theoretical tool to analyze and compare leadership performance on Social Networking Systems. While previous models mostly employed theme-based coding, this analytical tool relies on a set of structural indicators that enable a higher level of comparability across domains. To demonstrate, the LVPM will be employed to investigate the Instagram activity of Jeremy Corbyn and Boris Johnson during the 2019 UK General Election. Findings show how the LVPM indicators enable us to highlight differences in leadership style, compare them and employ them to build a typology.