Hashtag Hijacking Research Articles

Machine learning-based social media bot detection: a comprehensive literature review

In today’s digitalized era, Online Social Networking platforms are growing to be a vital aspect of each individual’s daily life. The availability of the vast amount of information and their open nature attracts the interest of cybercriminals to create malicious bots. Malicious bots in these platforms are automated or semi-automated entities used in nefarious ways while simulating human behavior. Moreover, such bots pose serious cyber threats and security concerns to society and public opinion. They are used to exploit vulnerabilities for illicit benefits such as spamming, fake profiles, spreading inappropriate/false content, click farming, hashtag hijacking, and much more. Cybercriminals and researchers are always engaged in an arms race as new and updated bots are created to thwart ever-evolving detection technologies. This literature review attempts to compile and compare the most recent advancements in Machine Learning-based techniques for the detection and classification of bots on five primary social media platforms namely Facebook, Instagram, LinkedIn, Twitter, and Weibo. We bring forth a concise overview of all the supervised, semi-supervised, and unsupervised methods, along with the details of the datasets provided by the researchers. Additionally, we provide a thorough breakdown of the extracted feature categories. Furthermore, this study also showcases a brief rundown of the challenges and opportunities encountered in this field, along with prospective research directions and promising angles to explore.

#DoctorsSpeakUp: Exploration of Hashtag Hijacking by Anti-Vaccine Advocates and the Influence of Scientific Counterpublics on Twitter

ABSTRACT The #DoctorsSpeakUp hashtag, which was designed by physicians to collectively promote vaccines on Twitter in Spring of 2020, was hijacked by anti-vaccine advocates. Through the lens of counterpublic sphere theory, thematic analysis revealed that the hashtag hijacking by a scientific counterpublic was successful, and the majority of #DoctorsSpeakUp tweets were oriented against vaccines. Five overarching themes emerged in anti-vaccine hijacked tweets, including: personal experience with vaccine injury, profits over people, lack of liability, perception that doctors are uninformed, and ‘We are the Herd.’ In contrast, fewer than 17% of tweets originated from pro-vaccine doctors who openly identified themselves as such in their tweets or profiles. Thus, using the #DoctorsSpeakUp hashtag, anti-vaccine advocates dominated the discourse, which speaks to the communication dynamics afforded within the information ecosystem of a social network. Hashtag activism can connect individuals and promote grassroots movements but may also backfire, allowing a vocal minority of individuals to shout the loudest through the digital megaphone.

Consumer mischief as playful resistance to marketing in Twitter hashtag hijacking

AbstractWhile both brand advocacy and protest have long been theorised as key facets in consumers' behaviour, we submit that in the participatory culture of social media, where consumers are free to create and publish their own content, the mischievous play has also become an inevitable form of online culture that brands must deal with. Drawing from Caillois' sociology of play and the cultural power model, we explore how consumers may playfully hijack brands' User‐Generated‐Content (UGC) hashtag campaigns. Based on a non‐participatory netnography, we observed consumers' tweets to unpack their playfulness in responding to brands' marketing communication messages on Twitter and then theorised how consumers use mischief as a form of resistance against marketing practice rather than brands themselves.

Habermasian utopia or Sunstein's echo chamber? The ‘dark side’ of hashtag hijacking and feminist activism

AbstractSociety thinks, talks, and communicates in ways which are inherently different now from the pre-Internet era. Hashtags in particular have transformed community formation around a particular topic, issue, or goal. A new and relatively under-studied phenomenon is that of ‘hashtag hijacking’, where individuals or groups use a particular hashtag to draw attention to arguments and narratives which undermine or oppose the hashtag's objective. Most of the current literature looks at hashtag hijacking as a positive outlet for counter-discourse/counter-narratives to challenge dominant groups. This study, however, looks at the ‘dark side’ of hashtag hijacking, where groups use trolling tactics similar to the Alt_Right to reinforce misogynistic views. The hijacking of three hashtags is explored in this study: #notacriminal, #women2drive, and #mydressmychoice, to explore feminist theories on the role of social media in a ‘public space’. Does Twitter function as one common public sphere where inequalities are so deeply embedded that minority voices have no hope of being heard? Or does Twitter function as a meeting place for multiple competing public spheres, thus allowing minority – and in this case feminist – voices to be heard?

Hashtag hijacking and crowdsourcing transparency: social media affordances and the governance of farm animal protection

The post-war Western world has seen a gradual shift from government to governance, a process that also concerned the issues related to agro-food sustainability, such as food quality, environmental impact, social justice, and farm animal welfare. Scholars believe that social media are a new site that reconfigures relations between various actors involved in the governance of these problems. However, empirical research on this matter remains scarce. This paper fills this gap by examining the case of Februdairy, a Twitter hashtag campaign to promote the British dairy industry, hijacked by animal protection activists. For this case, I employ the relational perspective on technology affordances—as operationalised by Faraj and Azad (in: Leonard et al. (eds), Materiality and organizing. Social interaction in a technological world, Oxford University Press, Oxford, 2012)—to highlight two distinct strategic modes of embracement of social media functionalities by the opposing groups: hashtag hijacking and crowdsourcing transparency. The analysis reveals also that a pre-existing social structure of the agro-food system conditions reconfiguration of social relations by technology in a way that actually strengthens the tendency to govern the issue of farm animal protection with market mechanisms.

We’ll always have purgatory: Fan spaces in social media

Abstract Certain groups within the fandom of the series Supernatural maintain that the network chronically fails to acknowledge or appreciate the support, discretionary income and above all unpaid affective labour of its young female audience – a viewership the series creators never anticipated. Such fans then create their own ways of engaging with both the show’s content and its public relations, using social media to craft personal spaces of both resistance and pleasure. This article examines three such creative efforts: a Twitter hashtag hijacking in 2015, when the CW perhaps unwisely invited viewers to ‘#AskSupernatural’; the fan-proposed spin-off Wayward Daughters (whose online petition has upwards of 3600 signatures) and fan-created YouTube series Kevin’s Continued Winchester Gospel (starring former guest actor Osric Chau). These labour-intensive spaces, created primarily by young women, speak to these fans’ perception of being disregarded by network public relations as well as the narrative of the series itself and its ongoing treatment of fan-favourite characters, particularly female ones, whether omitted from storylines or written violently off the show. In unprecedented volume, fans have merged creativity with collective action to craft playful yet highly publicized and efficient responses to the show’s public relations misattunement with its own audience.

HashMiner: Feature Characterisation and analysis of #Hashtag Hijacking using real-time neural network

Online social media has become a vital platform to discuss common topics which are being categorised under a single name: Hashtag where people put their views, opinions and data. Thus hashtags have become a victim for spam, fake and un-related advertising content dissemination. In this paper we propose a novel approach designed on 9 distinctive parameters which extends to 4 other derived statistic from Twitter Streaming API, to detect Hashtag hijacking using Neural network analysis which shows a mean hijacking percentage of 28.5 over 10, 240 test tweets collected whereas, manual based annotation performed results in 17.14 %hijacking.Our method over collected dataset results in 94.025% accuracy.

Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms

Many commercial products and academic research activities are embracing behavior analysis as a technique for improving detection of attacks of many sorts—from retweet boosting, hashtag hijacking to link advertising. Traditional approaches focus on detecting dense blocks in the adjacency matrix of graph data, and recently, the tensors of multimodal data. No method gives a principled way to score the suspiciousness of dense blocks with different numbers of modes and rank them to draw human attention accordingly. In this paper, we first give a list of axioms that any metric of suspiciousness should satisfy; we propose an intuitive, principled metric that satisfies the axioms, and is fast to compute; moreover, we propose CrossSpot , an algorithm to spot dense blocks that are worth inspecting, typically indicating fraud or some other noteworthy deviation from the usual, and sort them in the order of importance (“suspiciousness”). Finally, we apply CrossSpot to the real data, where it improves the F1 score over previous techniques by 68 percent and finds suspicious behavioral patterns in social datasets spanning 0.3 billion posts.

Hashtag hijacking: What it is, why it happens and how to avoid it

Hashtag hijacking is a form of cyber content attack that arises in modern social media microblogging platforms. It occurs when a hashtag is used for a different purpose than the one originally intended, such as tagging messages with undesirable content and surfacing this content to a target audience. In marketing campaigns, hashtag hijacking can have a significant impact on a company’s brand and/or the success of a marketing campaign. Despite the practical importance of hashtag hijacking and its numerous citations in the popular media, there has been little academic literature dealing with this emerging topic. This paper presents a first study of this phenomenon from a practical yet academically oriented perspective. Namely, it provides (1) a taxonomical classification of the different types of hashtag hijacking attacks; (2) a socio-technical data-mining methodology for detecting it at an early stage; and (3) a proposed response strategy informed by the traditional marketing literature.

‘How could anyone have predicted that #AskJameis would go horribly wrong?’ public relations, social media, and hashtag hijacking

This research explores how a Twitter public relations campaign was hijacked by audiences through an investigation of the #AskJameis campaign employed by Florida State University (FSU). A thematic analysis of 1214 tweets revealed that the hashtag was hijacked through audience members mocking and criticizing both FSU and Jameis Winston. The results suggest that PR professionals must account for the anticipated “pulse” of the audience before launching campaigns on social media. Underestimating the capabilities of the active social media audience can further exacerbate crisis situations, suggesting that at times, not using social media is a more effective public relations practice.

How “your hands look” and “what they can do”

Women use the #ManicureMonday Twitter hashtag to educate people about hand and nail care, share their nail art and expertise, and look at various hands. Beginning in 2013, the scientist Hope Jahren organized a hashtag hijacking in which scientists who were not in control of or associated with #ManicureMonday disrupted individuals' collaborative conversations about manicures, tried to educate participants, and expressed the scientists' values and interests. The scientists argued that what women's hands do is more important than how they look and that women and their manicured hands are constructed as passive objects on the Twitter feed. Jahren and these other scientists have identified Twitter as useful for their conversations about science and extended their own social capital by microblogging. They also use Twitter as a way to instruct women about objectification and other feminist issues and to intervene in women's interest in their nails, which these scientists believe is frivolous and disempowering. In this article, I address the diverse ways in which these ideas of usefulness, useful media, instruction, and social capital are articulated through #ManicureMonday by performing a close textual analysis of the manicure tweets and the hashtag hijacking. My reading is based on the relationship among feminist inquiries about viewing positions and objectification, the literature on useful media, and conceptions of social capital. I argue that we need to attend to the ways the #ManicureMonday hijacking and other instances of media education may not be useful for all participants.

HashJacker- Detection and Analysis of Hashtag Hijacking on Twitter

Social media has become a multi purpose platform where users tend to discuss their common topics of interest as well as utilise it for endorsement and campaigns.Twitter being one of the most widely used social media platforms,provides a mechanism known as Hashtag which enables diversified online users, having coinciding interests to connect with each other. Hashtagging a tweet provides the most effective way of promoting a content as it steadily acquires the reader’s attention because of it’s symbolic denotation.With increasing hits on a particular Hashtag, it comes under one of the ”trending topics”.Soon this trending topic becomes a line of sight for people using Twitter. Users tend to hijack these popular Hashtags for distributing un-related content, spam, negative sentiments to tarnish the intended motive of Hashtag making its presence counter-productive. We propose a tool: HashJacker which detects and analyses hijacking of Hashtag tweets.Also, we have discussed best practises to circumvent wrecked Hashtag tweets.