Profane Research Articles

Advancing offensive language detection in Arabic social media: a BERT-based ensemble learning approach

Advancing offensive language detection in Arabic social media: a BERT-based ensemble learning approach

Kajian Sosiolinguistik terhadap Tuturan Makian Masyarakat Heterogen di Medan

In general, humans interact to foster cooperation between each other to form, develop and pass on their culture in the broadest sense. In everyday life, of course, we don't just use formal language. When you are angry, the language used tends to be stiff and also has connotations. This research was conducted because swear words are not only used when angry, but swear words are also used in intimate and relaxed situations. Swear words also have the aim of insulting, belittling, expressing disappointment, admiration/surprise and praise. This research refers to a qualitative approach and uses two methods, namely the proficient free-involved listening method and the note-taking method. In this research, it is a method carried out by listening which is paralleled with observation, showing and studying carefully the object under study, the researcher records swearing in busy situations, the swearing data is then recorded in a data folio for analysis. The data analysis method used is the extralingual matching method. The results of the research show that Medan people mostly use swear words, almost eighty-five percent. Meanwhile, fifteen percent of Medan people use swear words in the form of phrases.

An Analysis of Men’s Language Features of an Dark Action Comedy on Prime Video

The purpose of the research titled "An Analysis of Gender in Language of a Dark Action Comedy on Prime Video" is to identify gendered language features applied in the series The data was collected using documentation method and was analyzed using qualitative method based on Jennifer Coates of men's language features as applied to the characters in the series "The Boys" episode 1 on Amazon Prime. The research identified several language features, including order versus proposal, swearing and taboo language, and interruptions, applied to the characters in the series. The main characters, Hughie and Hugh Campbell Sr., predominantly exhibited these features. Hughie used direct forms of address, swear words, and interruptions in his speech. Other characters in the series also displayed men's language features and differences in their language use.

Swear Words Used by Students in Daily Communication

This research focuses on 1) the classification of swearing sources used by students of STBA JIA and 2) the classification of the use of swearing proposed by students of STBA JIA. The theory used in this research is Wardhaugh's theory (1986:230); Hughes (1991:208); Rothwell (1973:108); Trudgill (1983) to classify sources and reasons or functions of swearing. This research is qualitative with descriptive methods. The data taken came from questionnaire answers by respondents consisting of 14 male students and 43 female students. This research found that there are 12 sources of swearing used by male respondents and 12 sources of swearing used by female respondents. There are a total of 12 sources of invective, consisting of 7 sources based on experts and 5 new sources. Then, regarding the reasons for using swear words, male respondents stated 16 reasons and female respondents stated 18 reasons. The total number of reasons for using swear words in this study was 24. Furthermore, related to research findings based on the classification of swear words, there is no difference in the classification of sources and the reasons for using swearing words between the reasons for male respondents and the reasons for female respondents

Hierarchical Sentiment Analysis Framework for Hate Speech Detection: Implementing Binary and Multiclass Classification Strategy

A significant challenge in automating hate speech detection on social media is distinguishing hate speech from regular and offensive language. These identify an essential category of content that web filters seek to remove. Only automated methods can manage this volume of daily data. To solve this problem, the community of Natural Language Processing is currently investigating different ways of hate speech detection. In addition to those, previous approaches (e.g., Convolutional Neural Networks, multi-channel BERT models, and lexical detection) have always achieved low precision without carefully treating other related tasks like sentiment analysis and emotion classification. They still like to group all messages with specific words in them as hate speech simply because those terms often appear alongside hateful rhetoric. In this research, our paper presented the hate speech text classification system model drawn upon deep learning and machine learning. In this paper, we propose a new multitask model integrated with shared emotional representations to detect hate speech across the English language. The Transformer-based model we used from Hugging Face and sentiment analysis helped us prevent false positives. Conclusion. We conclude that utilizing sentiment analysis and a Transformer-based trained model considerably improves hate speech detection across multiple datasets.

Adult language education in the United States – Accessibility, affordability, and opportunity

Adult language education in the United States – Accessibility, affordability, and opportunity

Karakteristik Ungkapan Makian dalam Podcast Akun Youtube Deddy Corbuzier

This research examines the use of profanity in Deddy Corbuzier's YouTube podcasts in Indonesia. The study aims to analyze the structure, types, and purposes of cuss words used. Employing a qualitative approach with descriptive methodology, data was collected through observation and recording of words, phrases, and clauses containing profanity. The analysis revealed 95 instances of cuss words, with word form being the most common structure (77 instances). Five categories were identified: conditional, animal-related, object-related, body part-related, and profession-related, with conditional being the most frequent (46 instances). Four functions of cuss word usage were observed: conformity to group norms, insults, expressions of shock or threats, and articulation of intense emotions, with the latter being most prominent (33 instances). Cuss words in these podcasts primarily take the form of single words and serve to describe negative qualities or express emotions, particularly surprise. Notably, they are used for both negative and positive purposes, including humor, to enhance entertainment value in Corbuzier's infotainment-focused podcasts.

Making Assessment Real: Audrey Holland's Contributions to the Assessment of Aphasia and Cognitive-Communication Disorders in Clinical and Research Settings.

For half a century, Dr. Audrey Holland investigated, developed, and implemented ways to extend the assessment of adult language and cognitive-communication disorders beyond traditional impairment-based approaches. This article summarizes Dr. Holland's many groundbreaking contributions to assessment practices by describing and exemplifying major conceptual and measurement innovations that have emerged from her research of both formal and informal assessment techniques. Dr. Holland's assessment contributions encompass the development of many widely used measures of functional communication, discourse, and cognitive-communication abilities. She also contributed to the development of assessment principles that have become part of best-practice standards of care. Some of her most significant contributions include: Drawing attention to assessment within authentic functional contexts; highlighting connections between language, communication, related cognitive abilities, and broader aspects of health including quality of life; raising psychometric standards; and emphasizing the value of implementing multiple person-centered measurement techniques spanning formal and informal as well as quantitative and qualitative approaches. Dr. Holland's career-long commitment and contributions to developing more meaningful and authentic assessment practices have transformed our field and substantively elevated the quality of care and services that we are able to provide to all persons who are impacted by language and cognitive-communication disorders.

Swearing and gender dynamics in urban Surabaya: Understanding Gen Z’s swearing in Surabaya’s arek culture

Swearing in society is a multifaceted phenomenon influenced. The purpose of this research is to understand the context of swearing among Generation Z in Surabaya and the differences in swearing between male and female Gen Z individuals in Surabaya. This research uses qualitative research methods involving 45 Generation Z informants from Surabaya. The results of the research show that the decision by Gen Z Surabaya is influenced by emotional context, social norms, culture, and group bonding to strengthen social ties, express emotions, and maintain their unique identity. Male Gen Z in Surabaya use the swear word “jancuk” with a higher pitch and rarely modify it, while female Gen Z use it with a lower pitch and frequently modify it. The conclusions of this research are first, the context of swearing among Generation Z in Surabaya occurs in informal situations among close friends for joking, easing the atmosphere, and insulting to demean the conversation partner, all influenced by Arek culture. Secondly, the difference in swearing between male and female Gen Z in Surabaya is that male Gen Z often use a higher pitch and rarely use modified swear words, while female Gen Z do not always use a high pitch and often use modified swear words to maintain their image. The use of swearing by both male and female Gen Z within the Arek Surabaya culture demonstrates intimacy, openness, egalitarianism, and the absence of social distance.

Disparities in Documentation: Evidence of Race-Based Biases in the Electronic Medical Record.

Personal implicit biases may contribute to inequitable health outcomes, but the mechanisms of these effects are unclear at a system level. This study aimed to determine whether stigmatizing subjective terms in electronic medical records (EMR) reflect larger societal racial biases. A cross-sectional study was conducted using natural language processing software of all documentation where one or more predefined stigmatizing words were used between January 1, 2019 and June 30, 2021. EMR from emergency care and inpatient encounters in a metropolitan healthcare system were analyzed, focused on the presence or absence of race-based differences in word usage, either by specific terms or by groupings of negative or positive terms based on the common perceptions of the words. The persistence ("stickiness") of negative and/or positive characterizations in subsequent encounters for an individual was also evaluated. Final analyses included 12,238 encounters for 9135 patients, ranging from newborn to 104years old. White (68%) vs Black/African American (17%) were the analyzed groups. Several negative terms (e.g., noncompliant, disrespectful, and curse words) were significantly more frequent in encounters with Black/African American patients. In contrast, positive terms (e.g., compliant, polite) were statistically more likely to be in White patients' documentation. Independent of race, negative characterizations were twice as likely to persist compared with positive ones in subsequent encounters. The use of stigmatizing language in documentation mirrors the same race-based inequities seen in medical outcomes and larger sociodemographic trends. This may contribute to observed healthcare outcome differences by disseminating one's implicit biases to unknown future healthcare providers.

Emotional intelligence as a mechanism for the prevention of school aggression

This paper evaluated an emotional intelligence program applied to primary school children. The study was conducted with an experimental group and a control group, allowing for a comparison between the program and traditional methods. During the experiment, manifestations of aggression, such as anger, and foul language, among others, were observed, and these behaviors progressively improved until favorable results in the post-test. These results indicate that incorporating programs to develop emotional intelligence can markedly improve student behavior, strengthen peer and teacher relationships, and equip students with vital skills for their future professional and social lives.

Narrative alchemy: Co-creating a game-based extensive reading framework for adult language learners

Contextual analysis is an important skill for language acquisition. It involves deciphering complex linguistic relationships and patterns. This way, unknown vocabulary can be learned if presented within understandable contexts. Extensive reading is a common method for developing this skill but requires learner participation. This paper presents a game-based extensive reading framework designed to encourage participation through a co-created visual novel. The project’s key features are its feasibility and role as a language course supplement. The short-term goal is to increase participation, with the long-term aim of promoting habitual reading and fostering language curiosity. The study was conducted in two parts: first, educational experts (n = 5) tested the framework for acceptance and feasibility; second, it was implemented at a language school (n = 13). Results indicate high acceptance from educators and enjoyment from learners. Although there was no significant increase in test scores, students’ willingness to participate in homework activities improved significantly.

Police coercive actions and citizen complaints: a comparison of NYPD precincts

PurposeThis study explores the influence of police coercive actions during Stop, Question, and Frisk (SQF) encounters on citizen complaints of police misconduct in 76 precincts in New York City.Design/methodology/approachUsing data from NYPD's SQF reports, Citizen Complaint Review Board, and demographic measures, the analysis focuses on specific coercive actions (frisk, search, summons, physical force, and arrest) and their association with citizen complaints (excessive force, abuse of authority, discourtesy, and offensive language).FindingsBivariate and multivariate analyses revealed frequent lower-level coercive actions, such as frisks and summons, are linked to increased citizen complaints. Surprisingly, higher levels of coercive actions involving force and arrests do not substantially impact complaints, challenging conventional assumptions.Practical implicationsThe research underscores the importance of transparency, accountability, and positive police-community relations. Addressing precinct-specific characteristics influencing the relationship between coercive actions and citizen complaints is crucial for fostering a more constructive and accountable policing approach in New York City precincts.Originality/valueThis study challenges assumptions by providing a distinctive perspective on the impact of police coercive actions during SQF encounters on citizen complaints. The unexpected finding that higher levels of coercive actions, typically involving force and arrests, do not substantially impact complaints contributes to the discourse on police-community interactions, offering a nuanced understanding of the relationship between specific coercive actions and citizen complaints.

A corpus-based study of subtitling religious swear words from English into Arabic

Abstract Subtitling Hollywood films with religious taboo words for conservative and closed societies, such as an Arab society, is a difficult task. This study investigates the dominant religious terms and functions used in Hollywood films and to identify the dominant translation strategies used for them in Arabic subtitles and determines whether these strategies are source language-oriented or target language-oriented (domesticating or foreignising). A corpus of 90 Hollywood films released between 2000 and 2018 is used to answer these questions; insights from descriptive translation studies are also taken (Toury, 2012). The corpus is analysed quantitatively and qualitatively using a self-designed, parallel and aligned corpus of 90 films and their Arabic subtitles. Findings reveal that the functions of religious taboo words have significant impacts on the choices of subtitling strategies. Foreignization strategies are used in roughly two-thirds of all occurrences of religious taboo words despite the cultural distance between English and Arabic. Using Modern Standard Arabic in Arabic subtitles limits subtitlers’ linguistic options. Furthermore, the nature of audio-visual translation influences subtitler choices because the meaning of a word can appear on the screen as a gesture, image or sound.

Control or coexist with urban baboons: Exploring residents' views and values in Cape Town

AbstractHumans and wildlife increasingly share urban space, which elevates the risk of negative interactions. Management efforts conventionally focus on controlling species that are considered problematic, but polarization in affected communities' perceptions and values may pose a greater problem for management in cities where ideas about preferred human–wildlife interactions vary greatly. This study uses Q‐method to investigate what type of human‐baboon relations are desirable among residents from seven areas in Cape Town regularly visited by chacma baboons. Two main perspectives emerged, each is motivated by a distinct set of values: 'Live with Baboons' is focused on positive outcomes for nature and society, recognizing humans' responsibility to mitigate negative interactions; whereas 'Control and Manage Baboons' views nature as something that should be controlled in order to maintain a stable and safe human society. Despite differences, the two perspectives also agree in rejecting abusive language toward baboons, recognizing that contexts differ and require different solutions, and acknowledging that resolving conflict requires collaboration. This has important bearing for recent public engagement processes led by local authorities to review management strategies. Residents' values and perceptions are manifestations of different lived realities and actively engaging with them can help to nuance dichotomies in the baboon discourse.

Beyond Swear Words: A Rhetorical Probing of Expletives Used in Filipino Movies

Beyond Swear Words: A Rhetorical Probing of Expletives Used in Filipino Movies

THE ANALYSIS OF STRATEGIES IN TRANSLATING SWEAR WORDS IN FREE GUY MOVIE SUBTITLE

This research aims to analyze the types of swear words and translation strategies used by translators in translating swear words in Free Guy movie. The data used in this research consists of subtitles from the movie in the form of words, phrases, clauses, and sentences. The film can be accessed via Disney+Hotstar.com and was released in 2021. The research adopts a descriptive-qualitative methodology and employs Anderson and Trudgill's theory on swear word and Baker's theory on translation strategies. The results of the research indicate that a total of 85 swear words. The most frequent type of swear word is expletive swearing with 55 data (64.70%). The second most common type is abusive swearing with 15 data (17.64%). Auxiliary swearing has 9 data (10.58%), and the least frequent is humorous swearing with 6 data (7.05%). In terms of translation strategies, there are four strategies were identified. The most frequently used strategy is translation using a more neutral meaning with 34 data (40%). The second most common strategy is translation using common words with 25 data (29.41%). Translation by omission has 21 data (24.70%), and the least frequent strategy is paraphrasing using related words with 5 data (5.88%). The high occurrence of expletive swearing is attributed to the characters expressing their emotions or feelings rather than intending to intimidate, insult, or joke. The translation strategy using more neutral or less expressive words is often employed by translators when they encounter difficulties in translating the cultural context from the SL to the TL.

The Impact of Harsh Parenting on the Self-efficacy of Chinese Middle School Students

As the level of education for all increases, family education is receiving more and more attention, and different parenting styles will have different impacts on children. This article mainly studies the impact of harsh parenting on Chinese middle school students' self-efficacy. In this study, 120 students of a middle school in Chengdu City, Sichuan Province, were recruited, and a questionnaire survey was conducted using stratified cluster sampling method, and 120 valid data were obtained. The questionnaire included the respondents' basic information, harsh parenting scale, and general self-efficacy scale, and the Cronbach's of the data was 0.76. Through comprehensive analyses, it is concluded that middle school students' self-efficacy was negatively correlated with their parents' harsh parenting, with the father's harsh language being the most significant in relation to the children's self-efficacy. In order to highlight the negative effects of harsh parenting and serve as a reminder to parents to be conscious of their own parenting style, this study aims to ascertain how strict parenting will impact children's sense of self-efficacy.

From hate to harmony: Leveraging large language models for safer speech in times of COVID-19 crisis

This study investigates the rampant spread of offensive and derogatory language during the COVID-19 pandemic and aims to mitigate it through machine learning. Employing advanced Large Language Models (LLMs), the research develops a sophisticated framework adept at detecting and transforming abusive and hateful speech. The project begins by meticulously compiling a dataset, focusing specifically on Chinese language abuse and hate speech. It incorporates an extensive list of 30 pandemic-related terms, significantly enriching the resources available for this type of research. A two-tier detection model is then introduced, achieving a remarkable accuracy of 94.42 % in its first phase and an impressive 81.48 % in the second. Furthermore, the study enhances paraphrasing efficiency by integrating generative AI techniques, primarily Large Language Models, with a Latent Dirichlet Allocation (LDA) topic model. This combination allows for a thorough analysis of language before and after modification. The results highlight the transformative power of these methods. They show that the rephrased statements not only reduce the initial hostility but also preserve the essential themes and meanings. This breakthrough offers users effective rephrasing suggestions to prevent the spread of hate speech, contributing to more positive and constructive public discourse.

Book Review - The Marketing of Academic, National and Public Libraries Worldwide: Marketing, Branding, Community Engagement

Patrick Lo and David Baker have brought the world of marketing to the center ground of libraries in their book The Marketing of Academic, National and Public Libraries Worldwide: Marketing, Branding, Community Engagement. Published by Chandos-Elsevier its sheer size and substance is indicative of how far the language, culture, and operations of marketing have taken root in the library sector worldwide and is in the minds of those who lead important libraries. Lo and Baker have captured an immense amount of information to fill a significant gap in the literature. Far from being a dirty word, the ‘marketing’ of libraries is clearly necessary, essential, desirable, perhaps uncomfortable at times, and quite fascinating.