Da'wah on Youtube is a part of the process of distributing da'wah messages through social media. The preachers use slang words in da’wah as a way to attract attention to audience, as personal ...identity, and to meet the standards of uses and gratification of the audience, even though they have to ignore the Qaulan ethics in da'wah. This study uses a qualitative descriptive method to describe several conditions, situations and phenomena of da'wah on Youtube. Sources of research data are documentation, online surveys and in-depth interviews related to the phenomenon of using slang words in da'wah. Based on the research results, it was found that the use of slang words in da'wah aims to attract the attention of the audience, establish the personal identity, and meet the standards of uses and gratification based on cognitive, affective, and behavioral levels of the audience. A positive reconstruction is needed to minimize the occurrence of distortions in the use of slang words and the Qaulan ethics in da’wah.
This study attempted to explore the process of word formation and its social function of slang words on Rich Brian's official music video, precisely in the comment section of the newest song of him, ...D.O.A that released on 25 August 2020. This study employed discourse and sociolinguistics aspects; hence, this study's research design was a descriptive qualitative. Additionally, this study's object was a one-month comment section of Rich Brian's newest song official music video. Furthermore, there were two sources of data, primary and secondary data sources. The primary data were a comment section of Rich Brian's newest official song music video, while the secondary source was from available works of literature and urban dictionary. Therefore, to collect the data, this study did the documentation from the D.O.A. official music video from one-month duration comments. As the data obtained, there were 49 slang words found. Then, they were analyzed through Yule (2010)’s theory as the basis of word formation process standard, while Zhou & Fan (2013)’s theory was used as the basis of word formation function standard. Data analysis is divided into several steps: reading, collecting, classifying, and analyzing the data. The result showed that derivation was the highest frequency of the word-formation process. It was 22%, the acronym was 18%, coinage was 16%, the conversion was 14%, blending was 12%, compounding was 8%, clipping was 6%, borrowing and multiple processes were 2% of each. Besides, the highest social function was to express emotive feeling with 49 % quantity of the frequency. The second higher was to pursue self-identity, achieving politeness was 8%. This study suggested a more in-depth analysis of non-standard languages, such as swear words or taboo words and emoticon that can be done through a social semiotic approach.
Internet slang words can very quickly become ubiquitous because of social memes and viral online content. Weibo, a Twitter‐like service in China, demonstrates that the adoption of popular Internet ...slang undergoes 2 distinct peaks in its temporal evolution, in which the former is relatively much lower than the latter. An in‐depth comparison of the diffusion of these different peaks suggests that popular attention in the early stage of propagation results in large‐scale coverage, while the participation of opinion leaders at the early stage only leads to minor popularity. Our empirical results question the conventional influentials hypothesis and provide some insights for marketing practice and influence maximization in social networks.
This paper focuses on the analysis of translation strategies of slang language as employed in the movie entitled “The Social Network”. This paper analyzes the translation strategies of the slang ...language from English into Indonesia from the movie entitled “The Social Network”. Baker’s translation strategies were used in this paper in order to analyze the data of this paper. The study findings reveal that there are 30 slang words used in this movie, and the subtitler adopted five translation strategies by Baker for translating the slang words in this movie. The analysis also reveals that most of the slang words in the movie have related words with the target language. There are no English slang words that were translated into Indonesia slang words in the movie. The subtitler mostly used the strategies for translating the English slang words into Indonesian words that have a similar expressive meaning. It can be interpreted as a result of the different culture of both countries that makes different slang words.
Abusive text (indiscriminate slang, abusive language, and profanity) on the Internet is not just a message but rather a tool for very serious and brutal cyber violence. It has become an important ...problem to devise a method for detecting and preventing abusive text online. However, the intentional obfuscation of words and phrases makes this task very difficult and challenging. We design a decision system that successfully detects (obfuscated) abusive text using an unsupervised learning of abusive words based on word2vec's skip-gram and the cosine similarity. The system also deploys several efficient gadgets for filtering abusive text such as blacklists, n-grams, edit-distance metrics, mixed languages, abbreviations, punctuation, and words with special characters to detect the intentional obfuscation of abusive words. We integrate both an unsupervised learning method and efficient gadgets into a single system that enhances abusive and non-abusive word lists. The integrated decision system based on the enhanced word lists shows a precision of 94.08%, a recall of 80.79%, and an f-score of 86.93% in malicious word detection for news article comments, a precision of 89.97%, a recall of 80.55%, and an f-score 85.00% for online community comments, and a precision of 90.65%, a recall of 93.57%, and an f-score 92.09% for Twitter tweets. We expect that our approach can help to improve the current abusive word detection system, which is crucial for several web-based services including social networking services and online games.
•We enhance abusive and non-abusive word lists based on learning algorithms and gadgets.•We design an effective abusive text detection system using both word lists.•We evaluate the system using real-world data and show its effectiveness.
The use of slang words in teenagers’ life is common in every country in the world. But in every country, each language is different in its words’ formation. The sources, as well as the formations of ...such words, are different from each country. The objectives of this study are 1) to find out the lists of slang words including abusive words used by Jakarta’s teenagers; 2) to analyze the morphological features of such slang words, and 3) to find out the negative impacts of using such slang words based on parents as well as school teachers’ opinions. The collected data in this research was analyzed and reported descriptively. The data are encrypted from the audio- recorders, questionnaires, and also taken from the interview session. The conclusion of this research is that there are ten word-formations of slang words used by Jakarta’s teenagers in their speaking with others daily. The researcher found out 558 slang words which are usually used by Jakarta’s teenagers in their daily speaking with their peers. The 558 words are grouped into 10 word-formation; they are reduplication (0.4%), clipping (3.9 %), onomatopoeia (4.5%), borrowing (4.8 %), other formation - backward letters and backward syllables (5.9 %), inflection (8.1 %), acronym (11.8 %), mixes / multiple processes (12.2 %), coinage (17.4 %), and blending (31 %). Out of 150 respondents – 100 school-teachers and 50 lecturers – there are 129 respondents (86%) who stated that there are negative impacts of using slang words by the students in their academic qualification in the learning process in the class they are teaching. This research is expected to be useful for all people around the world especially for the knowledge of linguists, lecturers, teachers as well as parents in order to know and understand the meaning of slang words used by teenagers in their speaking with their peers in their communication with others daily.
The article deals with the problem of the reverse influence of the Internet and chat communication on the spoken language based on the "Language of scum" in the Russian-speaking Internet. Today, this ...problem is relevant, since the development of the Internet has contributed to the widespread use of slang among the younger generation. The Internet today is a source of information. But the speed and availability of communication between users made it possible to use the Internet not only as a cognitive tool, but also as a means of communication and entertainment. And virtual communication, which arose due to the rapid development of the network, gave rise to a special language - the language of virtual communication. The numerous chats, open forums and personal pages created on the network are the main ways of communication among young people. Over the years, a special language has developed in the programs - slang, the so-called language of Internet communication, in which users communicate with each other. And every day he actively penetrates into our daily life. This study is a kind of appeal not only for adolescents, but also for the adult population. I would like people to think about the fact that we need to protect our language and not succumb to the influence of slang when communicating on social networks. The practical significance of the work lies in the fact that the results of this study will be useful to students in order to preserve their native language.
El artículo examina el problema de la influencia inversa de Internet y la comunicación por chat en
el idioma hablado basado en el "Idioma de la escoria" en Internet de habla rusa. Hoy en día, este
problema es relevante, ya que el desarrollo de Internet contribuyó al uso generalizado de la jerga
entre la generación más joven. Internet hoy es una fuente de información. Pero la rapidez y la
disponibilidad de la comunicación entre los usuarios hizo posible utilizar Internet no solo como
una herramienta cognitiva, sino también como un medio de comunicación y entretenimiento. Y la
comunicación virtual, que surgió debido al rápido desarrollo de la red, dio lugar a un lenguaje
especial: el lenguaje de la comunicación virtual. Los numerosos chats, foros abiertos y páginas
personales creadas en la red son las principales vías de comunicación entre los jóvenes. A lo largo
de los años, se ha desarrollado un lenguaje especial en los programas: la jerga, el llamado lenguaje
de la comunicación por Internet, en el que los usuarios se comunican entre sí. Y todos los días
penetra activamente en nuestra vida diaria. Este estudio es una especie de atractivo no solo para los
adolescentes, sino también para la población adulta. Me gustaría que la gente pensara en el hecho
de que debemos proteger nuestro idioma y no sucumbir a la influencia de la jerga cuando nos
comunicamos en las redes sociales. La importancia práctica del trabajo radica en el hecho de que
los resultados de este estudio serán de utilidad para los estudiantes con el fin de preservar su
lengua materna.
Sentiment information about social media posts is increasingly considered an important resource for customer segmentation, market understanding, and tackling other socio-economic issues. However, ...sentiment in social media is difficult to measure since user-generated content is usually short and informal. Although many traditional sentiment analysis methods have been proposed, identifying slang sentiment words remains a challenging task for practitioners. Though some slang words are available in existing sentiment lexicons, with new slang being generated with emerging memes, a dedicated lexicon will be useful for researchers and practitioners. To this end, we propose to build a slang sentiment dictionary to aid sentiment analysis. It is laborious and time-consuming to collect a comprehensive list of slang words and label the sentiment polarity. We present an approach to leverage web resources to construct a Slang Sentiment Dictionary (SlangSD) that is easy to expand. SlangSD is publicly available for research purposes. We empirically show the advantages of using SlangSD, the newly-built slang sentiment word dictionary for sentiment classification, and provide examples demonstrating its ease of use with a sentiment analysis system.
Sentiment analysis was a system for recognizing and extracting opinions in documents. There were two weaknesses in sentiment analysis. The first weakness was preprocessing in sentiment analysis can’t ...recognize slang words so that important words that should have been recognized became unrecognizable. The Second was the feature extraction process in sentiment analysis only recognized words based on the form of the word but can’t recognize the similar word. In this paper, we proposed spelling checker and wordnet to fix these weaknesses. We also used k-nearest neighbor (KNN), Naïve Bayes, and decision tree as methods for check classify the text. The purpose of this research was first to know the effects of used Wordnet and spelling checkers in sentiment analysis and second was to improve the data processing process in the existing sentiment analysis. The dataset that we used in the research was a list of tweets in Bahasa. The results showed wordnet and spelling checker make a decrease in the valued of false positives, false negatives, and true negatives in the calculation of the confusion matrix. It can increase the accuracy of the K-NN from 43% to 72%, Naïve Bayes from 41% to 71% and decision tree from 47% to 75%.
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