Twitter Hashtags Research Articles

Handouts don’t exist. Hustle or you don’t eat.

It is well established that AI has a bias problem; however, black-boxed machine learning systems render it difficult to even understand and visualize the nature and extent of the problem, let alone find solutions. This paper discusses an artistic research approach toward highlighting AI bias and explores the aesthetic potential of machine learning through a case study of an AI artwork called #RiseandGrind. The artist trained a recurrent neural network on a dataset extracted from Twitter hashtags (#Riseandgrind and #Hustle), which were selected to represent a specific filter bubble (embodied neoliberal precarity) in order to produce a biased AI that generates tweets for a Twitter bot. This paper unpacks how this artwork makes visible the processes of machine learning in a playful and poetic way. The work reveals how the original filter bias is consolidated, amplified, shaped, and ultimately codified through this machine learning process. The AI is found to reproduce a cohesive world view that, while reflecting the original data bias, further amplifies that bias through a process of flattening.

7.N. Workshop: Engaging the young stakeholders in planning for recovery from the Covid-19 pandemic

Health in children and young people (CYP) has been impacted by the COVID-19 pandemic. Restrictions in mobility and social contacts limited children and young people in their social development and led to adverse psychological impact. Rising rates of poverty because of lockdowns have been shown to particularly impact families with children, which may exacerbate already existing health inequalities. Containment policies have decreased access to health services and decreased support for CYP from health and social care professionals during the pandemic, which have posed a significant threat to children and young people's physical health, mental and emotional health. To ensure that policies aimed at mitigating the impact of the pandemic on CYP are relevant, it is vital that the voices of CYP are heard. Article 12 of UNCRC establishes the right of a child to express their views in all matters affecting them and for those to be given appropriate consideration. This is a right that is largely not upheld in policymaking, and therefore it is important that the public health sector as advocates for children and young people (CYP) lead on this.The aims of this skill building workshop are to: Showcase positive examples of engagement of CYP in policymakingGain knowledge on the practicalities to make engagement with CYP a mutually beneficial experience Workshop Format The session will be chaired by a young person to role-model the inclusion of CYP, this workshop advocates for.Professor Sonia Saxena, President of the EUPHA section on Child and Adolescent Public Health, will open the session with key points on the importance of engaging CYP in policy making during the COVID-19 pandemic and beyond.A further two presentations will be delivered by young people who will reflect on their own experience of engagement with policy/research and utilise the lessons learnt to improve CYP engagement in the future.This will be followed by a presentation by a paediatric doctor reflecting on their role in engaging with children and young people to develop a national healthcare patient experience guideline.This series of short presentations will be followed by an interactive case scenario on CYP engagement during the C-19 pandemic. The case study will aim to discuss some of the key practicalities to consider when engaging children and young people in policy making.The session will close with a short panel discussion with the presenters and consensus vote by attendees of next steps to take the learning from the workshop forward. Workshop proceedings will be written up and submitted for publication in a peer-reviewed journal. Twitter hashtags will be devised to allow attendees to share work they embark upon within an online community. This community will also be fostered through meetings supported by EUPHA where members can share best practice and solutions to problems encountered.Speakers/Panelists Sonia Saxena Imperial College London, London, UK Rakhee Shah Imperial College, London, UK Gabrielle Mathews Imperial College London, London, UK Bea Albermann University of Zurich, Zurich, Switzerland Jinane Ghattas UCLouvain, Saint-Josse-ten-Noode, Belgium Key messages COVID19 will have a large impact on children and young people’s health.Engaging children and young people to co-produce policies that affect them, when planning for recovery from the pandemic is crucial in ensuring our policies and research are most impactful.

“My freedom doesn’t care about your fear. My freedom doesn’t care about your feelings”: Postmodern and oppositional organizing in #OpenAmericaNow

In April 2020, amid the global COVID-19 pandemic, fringe political activists, conspiracy theorists, and far-right subcultures joined together to protest stay at home orders and social distancing decrees. Largely sharing information and organizing strategies on social media, these protestors adopted the Twitter hashtag #OpenAmericaNow to activate and mobilize supporters across the United States. In this study, we examine the online organizing of #OpenAmericaNow through analysis of 17,965 tweets to understand how fringe and conspiracy subcultures organized through oppositional consciousness raising. Our findings reveal multi-level discourses, which bridge identification on the micro-level with anti-elitist and post-truth logics on the macro-level. Theoretically, our study advances theorizing on postmodern organizing and conceptualizes alt-civic engagement, while also engaging in innovative methodological strategies useful for interrogating paradoxical and multi-level discourses.

A Critical Discourse Analysis of the Hashtag #WeAreAllIsraaGhrayeb on Twitter: An Exploration of Honor Killing Crimes in Palestine

AbstractThis research investigates a crucial social justice concern “honor killing” that are affecting women worldwide especially in Palestine. Feminist theory and critical theory provide a lens to explore issues of gender inequality, patriarchy, and oppression. The researcher utilized qualitative research method based on critical discourse analysis of the Twitter hashtag #WeAreAllIsraaGhrayeb between August 22 – September 22, 2019. Analyzing the tweets identified three themes: tweeters' anger and frustration against the killing of Israa Ghrayeb, the impact of honor killing crimes within the Palestinian community, and an urgent call for justice by action. The author is a participatory action researcher (PAR) who gained an experiential understanding and deeper insights of cultural relevance to address contemporary issues and to contextualize a cultural reality to benefit stakeholders (i.e., entities or individuals who witnessed the horrors of honor killing) by developing a strategic action plan that can bring social change leading to a just society.

Has the Rise of Socialism in U.S. Politics been a Boon to Austrian Economics? Evidence from Social Media and Other Metrics

The rise of socialism has been one of the more dramatic movements in US politics in the modern era, with recent Gallup polling indicating that 39 percent of Americans (and 65 percent of Democrats) hold a favorable view of the political economic ideology. Upward trends in the popularity of political economic ideologies such as socialism are observed when much of what is known by the public about them is gleaned through heuristic approaches rather than through scientific investigation. However, an increase in the persistence and severity of problems resulting from the practice of a political economic ideology such as socialism will likely lead to more science-based introspection, a turn in approach that will almost certainly be a boon to political and economic theories/models offering refutations of the ideology. This study explores such a demand-side argument with regard to the recent rise of socialism in US politics by asserting, and testing, the notion that the Austrian school of economics, which is most closely identified with the claim that socialism is unworkable, has been a beneficiary of recent political trends. Statistical evidence from various trends in informetrics is consistent with our assertion, as Google News hits and Twitter hashtag counts have ascended over the recent period (i.e., 2016 to 2019).

#ShamimaBegum: An analysis of social media narratives relating to female terrorist actors

This study explores the constructions of gender in social media narratives regarding Shamima Begum, a British born woman who travelled to Syria to join Islamic State of Iraq and Syria (ISIS). Using the Twitter hashtag #ShamimaBegum – developed in response to Begum’s expressed interest in returning to the United Kingdom to give birth to her third child – we employ critical discourse analysis to examine social media users’ responses to Begum’s case across a 3-week period. We portray how the vernacular narratives constructing femininity, gender, and their relation to terrorist activity are built on the expectation that the female actor should express remorse for her actions and is judged according to certain perceptions of maternalism, religion, and victimhood. We also explore the absence of considered agency in the narratives about women engaging in and disengaging from violent activities, demonstrating the weight of race, religion, and gender in shaping narratives surrounding perceived violent women.

Beacons over bridges: hashtags, visibility, and sexual assault disclosure on social media

ABSTRACT Aside from #MeToo and similar campaigns, sexual assault survivors use social media to disclose personal experiences. This paper uses a mixed-methods approach and draws on network ethnography (Howard, 2002) to explore the visibility of these ‘everyday’ sexual assault disclosures and how such disclosures further survivors’ disclosure motivations. Social network analysis of 23 Twitter hashtags related to sexual assault shows minimal engagement with disclosive tweets, while interviews with survivors (N = 27) indicate that hashtagged disclosures can result in impactful interactions with other survivors, particularly via less visible social media channels, such as direct messages. In combination, results suggest (1) that survivor networks can and do form around mundane hashtags, and (2) that highly visible hashtagged disclosures act as beacons to other survivors and are employed in pursuit of motivations such as supporting other survivors and challenging stigma associated with sexual assault.

Detection of Promoted Social Media Campaigns

Information spreading on social media contributes to the formation of collective opinions. Millions of social media users are exposed every day to popular memes — some generated organically by grassroots activity, others sustained by advertising, information campaigns or more or less transparent coordinated efforts. While most information campaigns are benign, some may have nefarious purposes, including terrorist propaganda, political astroturf, and financial market manipulation. This poses a crucial technological challenge with deep social implications: can we detect whether the spreading of a viral meme is being sustained by a promotional campaign? Here we study trending memes that attract attention either organically, or by means of advertisement. We designed a machine learning framework capable to detect promoted campaigns and separate them from organic ones in their early stages. Using a dataset of millions of posts associated with trending Twitter hashtags, we prove that remarkably accurate early detection is possible, achieving 95% AUC score. Feature selection analysis reveals that network diffusion patterns and content cues are powerful early detection signals.

On Analyzing Hashtags in Twitter

Hashtags, originally introduced in Twitter, are now becoming the most used way to tag short messages in social networks since this facilitates subsequent search, classification and clustering over those messages. However, extracting information from hashtags is difficult because their composition is not constrained by any (linguistic) rule and they usually appear in short and poorly written messages which are difficult to analyze with classic IR techniques. In this paper we address two challenging problems regarding the meaning of hashtags — namely, hashtag relatedness and hashtag classification - and we provide two main contributions. First we build a novel graph upon hashtags and (Wikipedia) entities drawn from the tweets by means of topic annotators (such as TagME); this graph will allow us to model in an efficacious way not only classic co-occurrences but also semantic relatedness among hashtags and entities, or between entities themselves. Based on this graph, we design algorithms that significantly improve state-of-the-art results upon known publicly available datasets. The second contribution is the construction and the public release to the research community of two new datasets: the former is a new dataset for hashtag relatedness, the latter is a dataset for hashtag classification that is up to two orders of magnitude larger than the existing ones. These datasets will be used to show the robustness and efficacy of our approaches, showing improvements in F1 up to two-digits in percentage (absolute).

Don’t Let Me Be #Misunderstood: Linguistically Motivated Algorithm for Predicting the Popularity of Textual Memes

Prediction of the popularity of online textual snippets gained much attention in recent years. In this paper we investigate some of the factors that contribute to popularity of specific phrases such as Twitter hashtags. We define a new prediction task and propose a linguistically motivated algorithm for accurate prediction of hashtag popularity. Our prediction algorithm successfully models the interplay between various constraints such as the length restriction, typing effort and ease of comprehension. Controlling for network structure and social aspects we get a glimpse into the processes that shape the way we produce language and coin new words. In order to learn the interactions between the constraints we cast the problem as a ranking task. We adapt Gradient Boosted Trees for learning ranking functions in order to predict the hashtags/neologisms to be accepted. Our results outperform several baseline algorithms including SVM-rank, while maintaining higher interpretability, thus our model's prediction power can be used for better crafting of future hashtags.

What Sticks With Whom? Twitter Follower-Followee Networks and News Classification

In this paper we analyze Twitter as a news channel in which the network of followers and followees significantly corresponds with the message content. We classified our data into twelve topics analogous to traditional newspaper sections and investigated whether the spread of information depended upon the Twitter network of followers and followees. To test this, we mapped the social network related to each topic and calculated the occurrence of retweet and mention mes-sages whose senders and receivers were interconnected as followers and followees. We found that on average 10% of retweets (RT-messages) and 5% of direct mentions between users (AT-messages) in Twitter hashtags are sent and received by users interconnected as followers and followees. These figures vary considerably from topic to topic, ranging from 15%-19% within Technology, Special Events and Politics to 3%-5% within the categories Personalities and Twitter-Idioms. The results show that hard-news messages are retweeted by a considerably larger community of users interconnected as followers and followees. We then performed a statistical correlation analysis of the dataset to validate the classification of hashtag in news sections based on retweet connectivity.

Stuff IBMers Say: Microblogs as an Expression of Organizational Culture

In globally distributed enterprises, face-to-face communication of the norms and values underlying organizational culture may not be feasible. As a result, enterprises have turned to social media as a potential resource for acculturation, the process in which employees make sense of organizational culture. In this paper, we explore the emergence of a Twitter hashtag (#stuffibmerssay) to characterize user participation and content of the tagged tweets, and describe the motivation of active contributors. Our analysis reveals that participants tended to share often humorous observations of everyday work practices indicative of a highly technical global workforce and interviews with participants suggested that the resulting tweets help reinforce a shared sense of group identity with other members of the organization. We conclude by discussing the implications of emergent social media as expressions of organizational culture, particularly when it occurs outside of the intranet.

Charting closed-loop collective cultural decisions: from book best sellers and music downloads to Twitter hashtags and Reddit comments

Charts are used to measure relative success for a large variety of cultural items. Traditional music charts have been shown to follow self-organizing principles with regard to the distribution of item lifetimes, the on-chart residence times. Here we examine if this observation holds also for (a) music streaming charts (b) book best-seller lists and (c) for social network activity charts, such as Twitter hashtags and the number of comments Reddit postings receive. We find that charts based on the active production of items, like commenting, are more likely to be influenced by external factors, in particular by the 24 h day–night cycle. External factors are less important for consumption-based charts (sales, downloads), which can be explained by a generic theory of decision-making. In this view, humans aim to optimize the information content of the internal representation of the outside world, which is logarithmically compressed. Further support for information maximization is argued to arise from the comparison of hourly, daily and weekly charts, which allow to gauge the importance of decision times with respect to the chart compilation period.

Analyzing the State of Digital Information Warfare Between India and Pakistan on Twittersphere

In this study, we analyze the state of information warfare on Twittersphere between India and Pakistan in the wake of Pulwama attack in Kashmir region and the subsequent surgical strikes by Indian forces inside Pakistan. We selected two leading Twitter hashtags on the conflict from the two countries each. A total of 20,000 tweets were manually analyzed. Contrary to the existing scholarship on digital information warfare, we found citizens from both countries produced most of the content. Among the citizens, those Twitter handles that showed affiliations with the heads of governments that we consider as trolls were the leading contributors. Moreover, the study found that contributors from the two countries mainly posted on their own hashtags and did not engage in counter-arguments with the contributors from other country. This resulted in overwhelming support for the two countries in their own assorted hashtags and outright criticism in the hashtags originating from the other country.

Sharing and self-promoting: An analysis of educator tweeting at the onset of the COVID-19 pandemic

Researchers have documented an array of ways Twitter hashtags offer digital spaces where educators can connect around interests and needs. During the early days of the COVID-19 pandemic, educators tweeted using various pandemic-related Twitter hashtags. In this study, we analyze data from two such hashtags: #remoteteaching and #remotelearning. We first data mined more than 36,000 tweets and then analyzed a random sample of 1,148 tweets and the accounts which sent those tweets. Our results suggest that the hashtags functioned as spaces in which a variety of education stakeholders engaged in activities that included knowledge sharing, social sharing, and information broadcasting. Alongside and sometimes entangled with such sharing, there was also a great deal of self-promotion. We discuss how these spaces appeared to offer potential benefits to educators navigating the transition to remote teaching but also consider how the presence of self-promotion may suggest downsides to such social mediums. We conclude with implications of these findings for education stakeholders and future research.

Exploring narrative linearity between Twitter and the news: Echoes of the Arab Spring in Brazil

This article explores the use of narrative theory as an analytical framework to investigate the extent to which popular hashtags and the news can develop into intersecting stories. It juxtaposes the case of hashtag-based reports seen during the Arab Spring to understand the coverage of notorious political episodes in Brazil. Namely, the 2016 impeachment of Dilma Rousseff and the 2018 election of Jair Bolsonaro. Here, narrative linearity emerges as a tool to observe the borrowing of Twitter hashtags in several journalistic pieces. It is contended that the linearity of authorship, narration and representation of time appears as a satisfactory pathway to trace the development of hashtags into popular news stories. Results suggested that hashtags can significantly follow narratives and agendas in journalism but differing from their original social media context.

Academic, social, and cultural learning in the French #bac2018 Twitter hashtag.

Despite the continued use of social media in educational contexts, there remains skepticism about whether platforms like Twitter can actually contribute to learning. In this paper, we argue that such skepticism is based on an overly narrow conception of learning that focuses on academic performance and disregards other manifestations. To advance this argument, we document use of the #bac2018 Twitter hashtag in the month leading up to the 2018 baccalauréat exams (the “bac”), which are significant not only for their role in the French educational system but also for their connections with broader French society and culture. We found that participants engaged in sharing notes; slacking, doubting, and fearing; requesting retweets; preferring topics; complaining; connecting with bac heritage and experience; joking; and showing awareness of time. In keeping with the significance of the bac, we found that these practices within the #bac2018 hashtag were associated with not only academic learning but also social and cultural practices that are significant despite their absence from any formal curriculum. These findings underline the complexity and richness that characterizes learning—especially in digital contexts.

Feminist Digital Counterpublics: Challenging Femicide in Kenya and South Africa

What happens when misogyny leads to increasing murders of women, whose lives are considered not worthy because their respectability is under attack? What do feminists do in a global moment when antifeminist backlash emerges with fervor in politics, policy, and social spaces to reverse and challenge feminist progress? Rage happens. This article explores the role of rage in the development of African feminist digital counterpublics on Twitter. Through two Twitter hashtags, #MenAreTrash and #JusticeForSharon, I illuminate how anger emanating from increasing rates of femicide in Kenya and South Africa catalyzes the evolution of feminist communities of knowledge, solidarity, and resistance on Twitter. The rage illustrated in this article is considered in relation to longer histories of burnout and fatigue with nonresponse from the state and from male allies. Through these digital spaces, a process of building alliances and challenging antifeminist movements emerges. Feminist engagements around these hashtags are a site of concrete resistance against online misogyny as well as its material manifestations through femicide. In a context where antifeminist movements see digital spaces as sites to mobilize antifeminist sentiment, paying attention to digital feminist counterpublics is critical to understanding gender justice and freedom.

Viewing Omnibus Law's Policy in a Governance Ethics Perspective through Social Media Twitter

Social media can quickly help people interact with the Government and use technology to turn communication into interactive dialogue. This study looks at Omnibus Law policies from government ethics through social media Twitter hashtag (#) Omnibus law. The method used in this research is qualitative, then data is collected from the Twitter hashtag using Nvivo12 Plus to analyze the data. This study's results reveal that the Hashtag (#) Omnibus Law's effectiveness is proven to be efficient in viewing data analysis through information dissemination on Nvivo12 Plus on Twitter to see policies and responses from the public who use the Hashtag (#) Omnibus Law.

The influence of policy and context on teachers’ social media use

AbstractResearch on teachers’ use of social media has typically assumed that it is a) driven by a need for professional learning and b) best understood in terms of individual motivations. In this study, we use a dataset of nearly 600,000 tweets posted to one or more of 48 Regional Educational Twitter Hashtags associated with 44 U.S. states. To explore the influence of local contextual factors on hashtag‐ and account‐level activity in these hashtags, we use an analytic approach heretofore uncommon in social media‐focussed education research: generalised linear and multilevel modelling. At the hashtag level, higher numbers of teachers within a state, proportions of students receiving subsidised meals, student‐to‐teacher ratios, and amounts of state spending per child are associated with more activity within a regional hashtag; by contrast, more left‐leaning state governments and citizenries are associated with less activity. At the account level, more experienced accounts and accounts in more right‐leaning states contribute more tweets to these hashtags. These findings reinforce established understandings of Twitter as a site for teacher learning; however, they also underline the importance of acknowledging other important purposes of teachers’ Twitter use, including receiving emotional support and engaging in activism.Practitioner notesWhat is already known about this topic Many teachers use Twitter (and other social media platforms) for professional purposes. Teachers have identified professional learning—among other purposes—as motivating their use of Twitter. Regional Educational Twitter Hashtags are diverse learning spaces for teachers and other education stakeholders. What this paper adds Local context and policy factors help influence teachers’ use of Twitter. Teachers may turn to Twitter because of a lack of emotional or political support—not just a lack of material support or professional development opportunities. Individual and idiosyncratic factors remain important in explaining teachers’ engagement with social media. Implications for practice and/or policy Informal spaces like social media may supplement formal support mechanisms for teachers. Teachers’ use of social media may help administrators and policymakers identify existing gaps to be repaired in those formal support mechanisms. Support for teachers should be conceived holistically and include emotional and political support.