Researching heritage values in social media environments:Understanding variabilities and (in)visibilities

This article adopts a reflexive methodology, called rapid logging, to examine how heritage values relating to the same heritage ‘thing’ are variously crafted by the mutual agencies of human and non-human actors on and with social media. In the process, it also explores the (in)visibilities produced through the heritage value assemblages co-curated by researchers with other actors including social media platforms and data, past objects, places and practices. The analysis focuses on the values associated with a specific case study, the area once occupied by the Old Gas Works, in North Canongate, Edinburgh, UK. Our conclusions demonstrate the importance of multi-platform and reflexive research to develop contextual and critical understandings of heritage value assemblages that can lead to fairer decision-making in heritage and more just societies

Islam as the Folk Devil : Hashtag Publics and the Fabrication of Civilizationism in a Post-Terror Populist Moment

With a focus on Twitter, this article investigates the populist moment triggered by a violent attack in the Northern European city of Turku, Finland, in August 2017. The article uses a mixed-method approach that applies a computational method for data collection and qualitative discursive mapping for data analysis. Moreover, the article applies Laclau's non-essentialist framework for theorizing on populism in connection to religion and critically discusses the types of religious implications identified in the "us" constructed in negation to Islam and the discursively constructed " bad" Muslim Other. The article suggests "civilizationism" and the related "Christianism" as potential schemas for advancing scholarly theorizing on the digital intersections between populism and religion, particularly in the present Northern European political context.Peer reviewe

Uptake, polymorphism, and the construction of networked events on twitter

This study conceptualises networked events as a platform-oriented view of media events by initiating a taxonomy of bottom-up construction. Focusing on computer-mediated event construction that may involve live delivery, permeate digital platforms, and attract user engagement prior to, during, and after the occurrence of ceremonial or disruptive events, the study argues that networked events can be characterised by polymorphism— i.e., presence of distinct patterns of uptake and different interactional orientations within the same space of interactions, such as hashtags. For analysis, a network dataset was created using 221,105 retweets that included the hashtag #HimToo. This hashtag was used extensively during the US Senate judiciary committee hearing that investigated claims of sexual harassment against President Trump's Supreme Court nominee Brett Kavanaugh. The study demonstrates that three types of construction— i.e., actor-centric, memetic, and metaconstruction— causes polymorphism in Twitter engagement related to the event

"Visual Affluence" in social photography: applicability of image segmentation as a visually oriented approach to study Instagram hashtags

The aim of the study is to examine the applicability of image segmentation – identification of objects/regions by partitioning images – to examine online social photography. We argue that the need for a meaning-independent reading of online social photography within social markers, such as hashtags, arises due to two characteristics of social photography: 1) internal incongruence resulting from user-driven construction, and 2) variability of content in terms of visual attributes, such as colour combinations, brightness, and details in backgrounds. We suggest visual affluence- plenitude of visual stimuli, such as objects and surfaces containing a variety of colour regions, present in visual imagery- as a basis for classifying visual content and image segmentation as a technique to measure affluence. We demonstrate that images containing objects with complex texture and background patterns are more affluent, while images that include blurry backgrounds are less affluent than others. Moreover, images that contain letters and dark, single-colour backgrounds are less affluent than images that include subtle shades. Mann-Whitney U test results for nine pairs of hashtags showed that seven out of nine pairs had significant differences in visual affluence. The proposed measure can be used to encourage a ‘visually oriented’ turn in online social photography research that can benefit from hybrid methods that are able to extrapolate micro-level findings to macro-level effects

The construction of the meanings of #coronavirus on Twitter: An analysis of the initial reactions of the Italian people

The first months of 2020 saw the coronavirus pandemic explode. Moving from China, it arrived in Europe and hit Italy. The place where the debate around it exploded was the media ecosystem. In a short time, it was an explosion of tweets related to the hashtag #coronavirus on Twitter. With the aim of reconstructing the meanings of the hashtag and the content, in terms of sentiment and opinions, of the reactions of the Italians, we collected in a large size corpus, the hundred thousand Italian tweets containing the #coronavirus produced during the media hype period from the Twitter repository (February 24th - 28th, 2020). Media hype period was discovered by digging in the online articles of ‘la Repubblica', based on the presence of the words: coronavirus and Italy. The media hype is February 26th. The corpus underwent Emotional Text Mining (ETM), an unsupervised methodology, which allows social profiling based on communication. The study of the word chosen to talk about a topic and their co-occurrence allows the understanding of people’s symbolizations, representations, and sentiment, about the coronavirus. In a retrospective logic, this mechanism allows us to reconstruct the sensemaking and nuances of meaning attributed by users to the coronavirus hashtag

#HimToo and the networking of misogyny in the age of #MeToo

This article brings together a quantitative approach which seeks to map and understand actor centrality and connectivity in relation to Twitter using social network analysis, with a qualitative set of interdisciplinary concerns around media representations of men's sexual violence against women. Our focus is #HimToo, a short-lived Twitter-backlash to #MeToo concentrated around the Brett Kavanaugh hearings and confirmation. We explore how #HimToo flourished and floundered across two key periods: the first related to the broadcast confirmation hearings; the second a backlash triggered by a Kavanaugh-supporting mom. With a dataset of over 277,000 Tweets, we argue that the first period shows an actor-centric conservative engagement which is dominated by female commentators, but displays a male-orientation that Kate Manne (2018) has described as himpathy. The second period presents both a serious and satirical response to the first. Whilst there is a significant reorientation of both activity and actors in this second period, we identify persistent gendered and generational patterns which warrant a more cautious response from feminist critics. We thus connect our analysis to debates about social media connectedness, gendered patterns of social media ab/use, and the role of social media in a highly polarised political climate in the USA

Interpreting the changeable meaning of hashtags: Toward the theorization of a model

This study contributes to the international debate on the hashtag's nature and characteristics and attempts to define it as a relational social form affected by morphogenetic–morphostatic processes. To develop this interpretative proposal, this study uses the dimensions of time and agency, drawing on Twitter hashtag studies. Subsequently, the article recalls elements of cultural morphogenesis, traces the points of contact between hashtag studies and cultural morphogenesis, constructs an interpretative proposal of the hashtag as a relational social form, and arrives at the formalization of a model for analyzing the changing meaning of hashtags

A template for mapping emotion expression within hashtag publics

Current literature on networked publics lacks research that examines how emotions are mobilised around specific actors, and quantitative analysis of affective phenomena is limited to vanity metrics. We address this issue by developing a network analytic routine, which guides the attribution of emotions contained in hashtagged tweets to their sources and targets. The proposed template enables identification of networked inconsequentiality (i.e., inability to trigger dialogue), reply targets (i.e., individuals targeted in replies), and voice agents (i.e., senders of replicated utterances). We demonstrate this approach with two datasets based on the hashtags #Newzealand (n= 131,523) and #SriLanka (n= 145,868) covering two major incidents of terrorism related to opposing extremist ideologies. In addition to the methodological contribution, the study demonstrates that user-driven emergence of networked leadership takes place based on conventional structures of power in which individuals with high power and social status are likely to emerge as targets as well as sources of emotions

Lockdown and Breakdown in Italians' Reactions on Twitter during the First Phase of Covid-19

The article focuses on Italians' reactions to the pandemic on Twitter. During the first phase of the 2020 lockdown (from the beginning of March 2020 - to the beginning of May 2020), a real-time dataset was built, linking data scratching to three events related to the introduction of the Prime Minister's decrees and his press conferences. The chosen observation point is Twitter, platform that allows us to monitor the emergence of discussions on public issues, extremely synchronized with events and news – which is, moreover, a feature of use of this platform. The coronavirus hashtag was chosen as a mechanism to track the development of Italian reactions, following the evolution of its sense and sensemaking and considering it as a polysemic collector. The aim is to identify within the tweets the actors, the topics, and the tone of the debate in an open public space. Furthermore, the analysis is carried out in search of the Italians' perception of the lockdown and whether they are in favor of it because of the defense of public health or they see it as a restriction of their individual freedom. The analysis, which used the socio-constructivist approach of Emotional Text Mining, reveals two explanatory-dimensions in the governance of the crisis: lockdown and breakdown and allows us to understand the reasons for Twitter's instinct-reactions

Lockdown and Breakdown in Italians' Reactions on Twitter during the First Phase of Covid-19

The article focuses on Italians' reactions to the pandemic on Twitter. During the first phase of the 2020 lockdown (from the beginning of March 2020 - to the beginning of May 2020), a real-time dataset was built, linking data scratching to three events related to the introduction of the Prime Minister's decrees and his press conferences. The chosen observation point is Twitter, platform that allows us to monitor the emergence of discussions on public issues, extremely synchronized with events and news – which is, moreover, a feature of use of this platform. The coronavirus hashtag was chosen as a mechanism to track the development of Italian reactions, following the evolution of its sense and sensemaking and considering it as a polysemic collector. The aim is to identify within the tweets the actors, the topics, and the tone of the debate in an open public space. Furthermore, the analysis is carried out in search of the Italians' perception of the lockdown and whether they are in favor of it because of the defense of public health or they see it as a restriction of their individual freedom. The analysis, which used the socio-constructivist approach of Emotional Text Mining, reveals two explanatory-dimensions in the governance of the crisis: lockdown and breakdown and allows us to understand the reasons for Twitter's instinct-reactions