Ethics in Pragmatics

This paper compiles a series of useful resources, which should act as pointers for decisionmaking processes for ethics in pragmatics.We show why ethical considerations are central to good academic practice, and key to protecting the interlocutors and informants whose practices we wish to study. In doing do, we advocate adopting an understanding of ethical decision making as a process, and not the result of a single decision made at the outset of research (cf. e.g., Markham and Buchanan, 2012). As we delineate in this chapter, this approach is key, given that there are not always straightforward, easy solutions to ethical desiderata. To ensure that scholars can benefit from the ethical-decision making processes other scholars have undergone, we thus advocate that scholars include brief discussions of the ethical measures underlining the research presented in their work. This transparency would serve to encourage a conversation among scholars within and across research disciplines and for greater recognition of the importance and relevance of seeing ethics as a process

Interaction and transformation on social media: the case of Twitter campaigns

The increasing popularity of social media platforms creates new digital social networks in which individuals can interact and share information, news, and opinion. The use of these technologies appears to have the capacity to transform current social configurations and relations, not least within the public and civic spheres. Within the social sciences, much emphasis has been placed on conceptualizing social media’s role in modern society and the interrelationships between online and offline actors and events. In contrast, little attention has been paid to exploring user practices on social media and how individual posts respond to each other. To demonstrate the value of an interactional approach toward social media analysis, we performed a detailed analysis of Twitter-based online campaigns. After categorizing social media posts based on action(s), we developed a typology of user exchanges. We found these social media campaigns to be highly heterogeneous in content, with a wide range of actions performed and substantial numbers of tweets not engaged with the substance of the campaign. We argue that this interactional approach can form the basis for further work conceptualizing the broader impact of activist campaigns and the treatment of social media as “data” more generally. In this way, analytic focus on interactional practices on social media can provide empirical insight into the micro-transformational characteristics within “campaign communication.

Not just pretty faces, they have powerful voices too : celebrity discourse and the #MeToo movement

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Flexible and Mindful Self-Tracking: Design Implications from Paper Bullet Journals

Digital self-tracking technologies offer many potential benefits over self-tracking with paper notebooks. However, they are often too rigid to support people’s practical and emotional needs in everyday settings. To inform the design of more flexible self-tracking tools, we examine bullet journaling: an analogue and customisable approach for logging and reflecting on everyday life. Analysing a corpus of paper bullet journal photos and related conversations on Instagram, we found that individuals extended and adapted bullet journaling systems to their changing practical and emotional needs through: (1) creating and combining personally meaningful visualisations of different types of trackers, such as habit, mood, and symptom trackers; (2) engaging in mindful reflective thinking through design practices and self-reflective strategies; and (3) posting photos of paper journals online to become part of a selftracking culture of sharing and learning. We outline two interrelated design directions for flexible and mindful selftracking: digitally extending analogue self-tracking and supporting digital self-tracking as a mindful design practice

Forensics Writer Identification using Text Mining and Machine Learning

Constant technological growth has resulted in the danger and seriousness of cyber-attacks, which has recently unmistakably developed in various institutions that have complex Information Technology (IT) infrastructure. For instance, for the last three (3) years, the most horrendous instances of cybercrimes were perceived globally with enormous information breaks, fake news spreading, cyberbullying, crypto-jacking, and cloud computing services. To this end, various agencies improvised techniques to curb this vice and bring perpetrators, both real and perceived, to book in relation to such serious cybersecurity issues. Consequently, Forensic Writer Identification was introduced as one of the most effective remedies to the concerned issue through a stylometry application. Indeed, the Forensic Writer Identification is a complex forensic science technology that utilizes Artificial Intelligence (AI) technology to safeguard, recognize proof, extraction, and documentation of the computer or digital explicit proof that can be utilized by the official courtroom, especially, the investigative officers in case of a criminal issue or just for data analytics. This research\u27s fundamental objective was to scrutinize Forensic Writer Identification technology aspects in twitter authorship analytics of various users globally and apply it to reduce the time to find criminals by providing the Police with the most accurate methodology. As well as compare the accuracy of different techniques. The report shall analytically follow a logical literature review that observes the vital text analysis techniques. Additionally, the research applied agile text mining methodology to extract and analyze various Twitter users\u27 texts. In essence, digital exploration for appropriate academics and scholarly artifacts was affected in various online and offline databases to expedite this research. Forensic Writer Identification for text extraction, analytics have recently appreciated reestablished attention, with extremely encouraging outcomes. In fact, this research presents an overall foundation and reason for text and author identification techniques. Scope of current techniques and applications are given, additionally tending to the issue of execution assessment. Results on various strategies are summed up, and a more inside and out illustration of two consolidated methodologies are introduced. By encompassing textural, algorithms, and allographic, emerging technologies are beginning to show valuable execution levels. Nevertheless, user acknowledgment would play a vital role with regards to the future of technology. To this end, the goal of coming up with a project proposal was to come up with an analytical system that would automate the process of authorship identification methodology in various Web 2.0 Technologies aspects globally, hence addressing the contemporary cybercrime issues

Stroke Survivors on Twitter : Sentiment and Topic Analysis From a Gender Perspective

BACKGROUND: Stroke is the worldwide leading cause of long-term disabilities. Women experience more activity limitations, worse health-related quality of life, and more poststroke depression than men. Twitter is increasingly used by individuals to broadcast their day-to-day happenings, providing unobtrusive access to samples of spontaneously expressed opinions on all types of topics and emotions. OBJECTIVE: This study aimed to consider the raw frequencies of words in the collection of tweets posted by a sample of stroke survivors and to compare the posts by gender of the survivor for 8 basic emotions (anger, fear, anticipation, surprise, joy, sadness, trust and disgust); determine the proportion of each emotion in the collection of tweets and statistically compare each of them by gender of the survivor; extract the main topics (represented as sets of words) that occur in the collection of tweets, relative to each gender; and assign happiness scores to tweets and topics (using a well-established tool) and compare them by gender of the survivor. METHODS: We performed sentiment analysis based on a state-of-the-art lexicon (National Research Council) with syuzhet R package. The emotion scores for men and women were first subjected to an F-test and then to a Wilcoxon rank sum test. We extended the emotional analysis, assigning happiness scores with the hedonometer (a tool specifically designed considering Twitter inputs). We calculated daily happiness average scores for all tweets. We created a term map for an exploratory clustering analysis using VosViewer software. We performed structural topic modelling with stm R package, allowing us to identify main topics by gender. We assigned happiness scores to all the words defining the main identified topics and compared them by gender. RESULTS: We analyzed 800,424 tweets posted from August 1, 2007 to December 1, 2018, by 479 stroke survivors: Women (n=244) posted 396,898 tweets, and men (n=235) posted 403,526 tweets. The stroke survivor condition and gender as well as membership in at least 3 stroke-specific Twitter lists of active users were manually verified for all 479 participants. Their total number of tweets since 2007 was 5,257,433; therefore, we analyzed the most recent 15.2% of all their tweets. Positive emotions (anticipation, trust, and joy) were significantly higher (P<.001) in women, while negative emotions (disgust, fear, and sadness) were significantly higher (P<.001) in men in the analysis of raw frequencies and proportion of emotions. Happiness mean scores throughout the considered period show higher levels of happiness in women. We calculated the top 20 topics (with percentages and CIs) more likely addressed by gender and found that women's topics show higher levels of happiness scores. CONCLUSIONS: We applied two different approaches-the Plutchik model and hedonometer tool-to a sample of stroke survivors' tweets. We conclude that women express positive emotions and happiness much more than men

Turn and face the strange: Investigating filter bubble bursting information interactions

It is a 'truth universally acknowledged' that people prefer to minimize encounters with information they disagree with and ignore it where they find it. Algorithms purportedly support this avoidance by creating filter bubbles filled only with agreeable information potentially increasing polarisation and undermining democracy. How accurate is this portrayal, though? Recent research has begun to cast doubt. We challenge these assumptions and report a two-phase analysis of filter bubble-bursting behavior. The first phase reports novel incidental findings from an interview study on the role of information interaction in view change. Participants demonstrated a clear interest in a diversity of information, including information specifically opposed to their own views. The second phase reports findings from a diary study specifically designed to investigate people's interactions with information that reflected a different view to theirs. We examine how people found disagreeable information, how they responded to it and the factors affecting their responses. We find that people will sometimes actively seek and engage with disagreeable information, rather than avoid and ignore it. Our findings pave the way for future information interfaces that support this previously undiscussed information interaction

280 insulting characters? An analysis of the content of tweets addressed to the police in Canada and the United States

Travail dirigé présenté à la Faculté des arts et sciences en vue de l'obtention du grade de Maîtrise en criminologie, option criminalistique et information.Les réseaux sociaux tel Twitter sont de plus en plus populaires. Il n’est donc pas surprenant que la police s’engage sur ce terrain. Les réseaux sociaux permettent à la police de communiquer facilement avec la population dans un espoir d’amélioration de leur relation avec les citoyens qui peut parfois être tendue. Avec la démocratisation d’internet et l’avènement des réseaux sociaux, les incivilités qui auparavant étaient limitées au monde réel se sont transposées en ligne. La police est donc parfois la cible de ces cyber-incivilités. Bien que l’utilisation des réseaux sociaux par la police ait été étudié ces dernières années, la manière dont la population communique avec la police, surtout lorsqu’elle le fait de manière antagoniste, n’a été l’objet que de quelques recherches seulement. La présente étude cherche à combler ce manque dans la littérature en analysant ce qui est dit à la police sur le réseau social Twitter. Les tweets de janvier 2018 mentionnant les départements de police sélectionnés au Canada et aux Etats-Unis ont été collectés. Les résultats démontrent que certains départements de police sont plus mentionnés que d’autres (c’est que le cas du TPS et de la NYPD) mais aussi plus insultés que d’autres. La police se retrouve au milieu de tensions puisqu’elle est la cible de plusieurs insultes. Les tweets mentionnant la police ont les thèmes suivants : cas spécifiques, comportement de la police, politique, histoires locales mais sont également composés d’insultes gratuites, sans contexte. L’étude conclue que les tensions en ligne, qu’elles soient ponctuelles ou systématiques, répliquent les tensions locales déjà présentes hors ligne.Social media such as Twitter are becoming more popular. It is without surprise that the police would engage in this field. Social media allow the police to easily communicate with the population in the hope to ameliorate the relationship between the police and citizens, which can be tense at times. With the democratisation of the internet and the advent of social media, incivilities which were limited to the real world have been transposed online. The police are therefore sometimes the target of these cyber-incivilities. Even if the use of social media by the police has been studied in the last few years, the way the population communicates with the police, especially when they do in an antagonistic manner, has not been researched thoroughly. The present study aims to fill this literature gap by analysing what is said to the police on Twitter. Tweets from January 2018 mentioning the selected police departments in Canada and in the United States have been collected. The results show that some police departments are more mentioned than others (it is the case of the TPS and the NYPD) but also more insulted than others. The police are caught in the middle of tensions as they are the target of several insults. Tweets mentioning the police have the following themes: specific cases, police behaviour, politics, local news but are also comprised of plain insults, without context. The study concludes that online tensions, whether they are punctual or systematic, resonate the already existent offline local tensions

Exploring Sentiment Analysis on Twitter: Investigating Public Opinion on Migration in Brazil from 2015 to 2020

openTechnology has reshaped societal interaction and the expression of opinions. Migration is a prominent trend, and analysing social media discussions provides insights into societal perspectives. This thesis explores how events between 2015 and 2020 impacted Brazilian sentiment on Twitter about migrants and refugees. Its aim was to uncover the influence of key sociopolitical events on public sentiment, clarifying how these echoed in the digital realm. Four key objectives guided this research: (a) understanding public opinions on migrants and refugees, (b) investigating how events influenced Twitter sentiment, (c) identifying terms used in migration-related tweets, and (d) tracking sentiment shifts, especially concerning changes in government. Sentiment analysis using VADER (Valence Aware Dictionary and sEntiment Reasoner) was employed to analyse tweet data. The use of computational methods in social sciences is gaining traction, yet no analysis has been conducted before to understand the sentiments of the Brazilian population regarding migration. The analysis underscored Twitter's role in reflecting and shaping public discourse, offering insights into how major events influenced discussions on migration. In conclusion, this study illuminated the landscape of Brazilian sentiment on migration, emphasizing the significance of innovative social media analysis methodologies for policymaking and societal inclusivity in the digital age