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.
{"title":"Exploring leadership on Instagram","authors":"Michele Martini","doi":"10.33621/jdsr.v6i2.205","DOIUrl":"https://doi.org/10.33621/jdsr.v6i2.205","url":null,"abstract":"\u0000Online 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. \u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"8 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141099516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Özkula, Hadas Schlussel, Tom Divon, Danka Ninković Slavnić
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.
{"title":"Special Issue on Methods in Visual Politics and Protest","authors":"S. Özkula, Hadas Schlussel, Tom Divon, Danka Ninković Slavnić","doi":"10.33621/jdsr.v6i2.278","DOIUrl":"https://doi.org/10.33621/jdsr.v6i2.278","url":null,"abstract":"\u0000This 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.\u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"7 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141099200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Dwelling as Method","authors":"Brianna I. Wiens, Shana MacDonald","doi":"10.33621/jdsr.v6i2.211","DOIUrl":"https://doi.org/10.33621/jdsr.v6i2.211","url":null,"abstract":"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.","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"4 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141100899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Researching visual protest and politics with “extra-hard” data","authors":"S. Özkula, J. Omena, R. Gajjala","doi":"10.33621/jdsr.v6i2.214","DOIUrl":"https://doi.org/10.33621/jdsr.v6i2.214","url":null,"abstract":"\u0000A 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.\u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"46 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Understanding climate-related visual storytelling on TikTok","authors":"Jing Zeng, Xiaoyue Yan","doi":"10.33621/jdsr.v6i2.212","DOIUrl":"https://doi.org/10.33621/jdsr.v6i2.212","url":null,"abstract":"\u0000This 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.\u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"12 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141098618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article investigates engagement with propagandist TikTok videos shortly after Russia’s invasion of Ukraine on February 24, 2022, with particular attention to the role of music and comments. By repurposing the infrastructure of TikTok sound-linking, our research upholds sensitivity to how this infrastructure enables affective and participatory workings of propaganda. We develop the notion of networked masterplots based on a situated analysis of how a specific sound, occasionally used in combination with pro-Russian hashtags, prescribes the creation of replicable linkages between three distinct video templates. The analysed templates, as we will show, not only intentionally share the use of the same song but adapt the theatrical effect of situation and suspense on the textual level of “stickers” or messages overlaid on top of videos. A selection of fifteen videos using the stickers – “What if they attack?”, “I am wondering how many will (un)subscribe?”, and “I am (not) ashamed” – in combination with a techno remix of the Soviet folk song Katyusha will be at the centre of our investigation. Arguing that in Katyusha videos situation and suspense are indivisible, we pay attention to the audiencing practices as they extend into both video comment sections and further memetic spin-offs. We conclude by reflecting on how TikTok sharing not only facilitates self-expression and social activism but also enables the weaponization of content within networked memetic environments.
{"title":"Networked masterplots","authors":"M. Geboers, Elena Pilipets","doi":"10.33621/jdsr.v6i1.201","DOIUrl":"https://doi.org/10.33621/jdsr.v6i1.201","url":null,"abstract":"\u0000This article investigates engagement with propagandist TikTok videos shortly after Russia’s invasion of Ukraine on February 24, 2022, with particular attention to the role of music and comments. By repurposing the infrastructure of TikTok sound-linking, our research upholds sensitivity to how this infrastructure enables affective and participatory workings of propaganda. We develop the notion of networked masterplots based on a situated analysis of how a specific sound, occasionally used in combination with pro-Russian hashtags, prescribes the creation of replicable linkages between three distinct video templates. The analysed templates, as we will show, not only intentionally share the use of the same song but adapt the theatrical effect of situation and suspense on the textual level of “stickers” or messages overlaid on top of videos. A selection of fifteen videos using the stickers – “What if they attack?”, “I am wondering how many will (un)subscribe?”, and “I am (not) ashamed” – in combination with a techno remix of the Soviet folk song Katyusha will be at the centre of our investigation. Arguing that in Katyusha videos situation and suspense are indivisible, we pay attention to the audiencing practices as they extend into both video comment sections and further memetic spin-offs. We conclude by reflecting on how TikTok sharing not only facilitates self-expression and social activism but also enables the weaponization of content within networked memetic environments.\u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"16 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140263084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Omena, Thais Lobo, Giulia Tucci, Elias Bitencourt, Emillie de Keulenaar, Francisco Kerche, Jason Chao, Marius Liedtke, Mengying Li, Maria Luiza Paschoal, Ilya Lavrov
Computational social science research on automated social media accounts, colloquially dubbed “bots”, has tended to rely on binary verification methods to detect bot operations on social media. Typically focused on textual data from Twitter (now rebranded as "X"), these inference-based methods are prone to finding false positives and failing to understand the subtler ways in which bots operate over time, through visual content and in particular contexts. This research brings methodological contributions to such studies, focusing on what it calls “bolsobots” in Brazilian social media. Named after former Brazilian President Jair Bolsonaro, the bolsobots refer to the extensive and skilful usage of partial or fully automated accounts by marketing teams, hackers, activists or campaign supporters. These accounts leverage online political culture to sway public opinion for or against public policies, opposition figures, or Bolsonaro himself. Drawing on empirical case studies, this paper implements quali-quanti visual methods to operationalise specific techniques for interpreting bot-associated image collections and textual content across Instagram, TikTok and Twitter/X. To unveil the modus operandi of bolsobots, we map the networks of users they follow (“following networks”), explore the visual-textual content they post, and observe the strategies they deploy to adapt to platform content moderation. Such analyses tackle methodological challenges inherent in bot studies by employing three key strategies: 1) designing context-sensitive queries and curating datasets with platforms’ interfaces and search engines to mitigate the limitations of bot scoring detectors, 2) engaging qualitatively with data visualisations to understand the vernaculars of bots, and 3) adopting a non-binary analysis framework that contextualises bots within their socio-technical environments. By acknowledging the intricate interplay between bots, user and platform cultures, this paper contributes to method innovation on bot studies and emerging quali-quanti visual methods literature.
{"title":"Quali-quanti visual methods and political bots","authors":"J. Omena, Thais Lobo, Giulia Tucci, Elias Bitencourt, Emillie de Keulenaar, Francisco Kerche, Jason Chao, Marius Liedtke, Mengying Li, Maria Luiza Paschoal, Ilya Lavrov","doi":"10.33621/jdsr.v6i1.215","DOIUrl":"https://doi.org/10.33621/jdsr.v6i1.215","url":null,"abstract":"\u0000Computational social science research on automated social media accounts, colloquially dubbed “bots”, has tended to rely on binary verification methods to detect bot operations on social media. Typically focused on textual data from Twitter (now rebranded as \"X\"), these inference-based methods are prone to finding false positives and failing to understand the subtler ways in which bots operate over time, through visual content and in particular contexts. This research brings methodological contributions to such studies, focusing on what it calls “bolsobots” in Brazilian social media. Named after former Brazilian President Jair Bolsonaro, the bolsobots refer to the extensive and skilful usage of partial or fully automated accounts by marketing teams, hackers, activists or campaign supporters. These accounts leverage online political culture to sway public opinion for or against public policies, opposition figures, or Bolsonaro himself. Drawing on empirical case studies, this paper implements quali-quanti visual methods to operationalise specific techniques for interpreting bot-associated image collections and textual content across Instagram, TikTok and Twitter/X. To unveil the modus operandi of bolsobots, we map the networks of users they follow (“following networks”), explore the visual-textual content they post, and observe the strategies they deploy to adapt to platform content moderation. Such analyses tackle methodological challenges inherent in bot studies by employing three key strategies: 1) designing context-sensitive queries and curating datasets with platforms’ interfaces and search engines to mitigate the limitations of bot scoring detectors, 2) engaging qualitatively with data visualisations to understand the vernaculars of bots, and 3) adopting a non-binary analysis framework that contextualises bots within their socio-technical environments. By acknowledging the intricate interplay between bots, user and platform cultures, this paper contributes to method innovation on bot studies and emerging quali-quanti visual methods literature.\u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140261178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Research examining radical visual communication and its manifestation on the trending platform TikTok is limited. This paper presents a novel methodological framework for studying mobilization strategies of far-right groups on TikTok, employing a mixed-method approach that combines manual annotation, unsupervised image classification, and named-entity recognition to analyze the dynamics of radical visuals at scale. Differentiating between internal and external mobilization, we use popularity and engagement cues to investigate far-right mobilization efforts on TikTok within and outside their community. Our findings shed light on the effectiveness of unsupervised image classification when utilized within a broader mixed-method framework, as each observed far-right group employs unique platform characteristics. While Conspiracists flourish in terms of overall popularity and internal mobilization, nationalist and protest content succeeds by using a variety of persuasive visual content to attract and engage external audiences. The study contributes to existing literature by bridging the gap between visual political communication at scale and radicalization research. By offering insights into mobilization strategies of far-right groups, our study provides a foundation for policymakers, researchers, and online platforms to develop proactive measures to address the risks associated with the dissemination of extremist ideologies on social media. The study contributes to existing literature by bridging the gap between visual political communication at scale and radicalization research. By offering insights into mobilization strategies of far-right groups, our study provides a foundation for policymakers, researchers, and online platforms to develop proactive measures to address the risks associated with the dissemination of extremist ideologies on social media.
{"title":"Analyzing Radical Visuals at Scale","authors":"Julian Hohner, Azade E. Kakavand, Sophia Rothut","doi":"10.33621/jdsr.v6i1.200","DOIUrl":"https://doi.org/10.33621/jdsr.v6i1.200","url":null,"abstract":"\u0000Research examining radical visual communication and its manifestation on the trending platform TikTok is limited. This paper presents a novel methodological framework for studying mobilization strategies of far-right groups on TikTok, employing a mixed-method approach that combines manual annotation, unsupervised image classification, and named-entity recognition to analyze the dynamics of radical visuals at scale. Differentiating between internal and external mobilization, we use popularity and engagement cues to investigate far-right mobilization efforts on TikTok within and outside their community. Our findings shed light on the effectiveness of unsupervised image classification when utilized within a broader mixed-method framework, as each observed far-right group employs unique platform characteristics. While Conspiracists flourish in terms of overall popularity and internal mobilization, nationalist and protest content succeeds by using a variety of persuasive visual content to attract and engage external audiences. The study contributes to existing literature by bridging the gap between visual political communication at scale and radicalization research. By offering insights into mobilization strategies of far-right groups, our study provides a foundation for policymakers, researchers, and online platforms to develop proactive measures to address the risks associated with the dissemination of extremist ideologies on social media.\u0000\u0000The study contributes to existing literature by bridging the gap between visual political communication at scale and radicalization research. By offering insights into mobilization strategies of far-right groups, our study provides a foundation for policymakers, researchers, and online platforms to develop proactive measures to address the risks associated with the dissemination of extremist ideologies on social media.","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"14 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140262275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates how internet memes are complex and stratified objects, going beyond the standardized definition of ‘image macro’ habitually employed by scholars. To this end, we take the 2019 Italian government crisis as a case study and analyze a dataset of related 1.269 memes using a combination of computational and qualitative methodologies. Our analysis shows the emergence, proliferation, and fading of popular templates, which remix images and text from the political crisis and occasionally serve as frames for other events: the Contingent Macro. Together with less standardized memetic instances, we found that Contingent Macros concur to create metaphoric narratives, which develop as the event unfolds. Besides formalizing the concept of Contingent Macro, this work provides scholars with a methodological toolkit for the analysis of event-related meme production, which can capture the fluidity of memes. Overall, the article concurs to underline the need for a clear, context-specific definition of memes, tailored to specific social, cultural, and research contexts.
{"title":"The contingent macro","authors":"Giulia Giorgi, Ilir Rama","doi":"10.33621/jdsr.v6i1.202","DOIUrl":"https://doi.org/10.33621/jdsr.v6i1.202","url":null,"abstract":"\u0000This paper investigates how internet memes are complex and stratified objects, going beyond the standardized definition of ‘image macro’ habitually employed by scholars. To this end, we take the 2019 Italian government crisis as a case study and analyze a dataset of related 1.269 memes using a combination of computational and qualitative methodologies. Our analysis shows the emergence, proliferation, and fading of popular templates, which remix images and text from the political crisis and occasionally serve as frames for other events: the Contingent Macro. Together with less standardized memetic instances, we found that Contingent Macros concur to create metaphoric narratives, which develop as the event unfolds. Besides formalizing the concept of Contingent Macro, this work provides scholars with a methodological toolkit for the analysis of event-related meme production, which can capture the fluidity of memes. Overall, the article concurs to underline the need for a clear, context-specific definition of memes, tailored to specific social, cultural, and research contexts.\u0000","PeriodicalId":475991,"journal":{"name":"Journal of digital social research","volume":"42 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140261664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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