Social Media Translational Action

2022 ◽  
pp. 250-274
Author(s):  
Aznur Aisyah ◽  
Intan Safinaz Zainudin ◽  
Rou Seung Yoan
Keyword(s):  
Social Media ◽  
Pop Culture ◽  
Translation Studies ◽  
Data File ◽  
Multimedia Data ◽  
Translation Process ◽  
Twitter Account ◽  
Data Source ◽  
Internet Application ◽  
Original File

Internet application advancement has enabled Korean pop culture (K-Pop) to rapidly spread worldwide. However, technology alone is insufficient in delivering k-pop content to K-Pop fans because of language barriers. Hence, the translator's role is pivotal in decoding these data. Realising this crucial need, fans have acted as translators in interpreting enormous data file that have been improperly translated or unavailable in the original file. This research examined the translation process occurring in Twitter microblogging environment which is rarely analysed among linguistic scholars. the translation style of fan translators was identified, and the translational action involved discussed. K-Pop group, Bangtan Sonyeondan's (BTS) twitter account was selected as the main data source and Korean-English fan translation of the content distributed in the account was collected. The microblogging interface is equipped with the latest technology that supports multimedia data form, resulting in more dynamic translation work which needs to be highlighted in translation studies.

Social Media Translational Action

2019 ◽  
Vol 9 (2) ◽  
pp. 32-54
Author(s):  
Aznur Aisyah ◽  
Intan Safinaz Zainudin ◽  
Rou Seung Yoan
Keyword(s):  
Social Media ◽  
Pop Culture ◽  
Translation Studies ◽  
Data File ◽  
Multimedia Data ◽  
Translation Process ◽  
Twitter Account ◽  
Data Source ◽  
Internet Application ◽  
Original File

Internet application advancement has enabled Korean pop culture (K-Pop) to rapidly spread worldwide. However, technology alone is insufficient in delivering k-pop content to K-Pop fans because of language barriers. Hence, the translator's role is pivotal in decoding these data. Realising this crucial need, fans have acted as translators in interpreting enormous data file that have been improperly translated or unavailable in the original file. This research examined the translation process occurring in Twitter microblogging environment which is rarely analysed among linguistic scholars. the translation style of fan translators was identified, and the translational action involved discussed. K-Pop group, Bangtan Sonyeondan's (BTS) twitter account was selected as the main data source and Korean-English fan translation of the content distributed in the account was collected. The microblogging interface is equipped with the latest technology that supports multimedia data form, resulting in more dynamic translation work which needs to be highlighted in translation studies.

Is JUUL marketing to kids on social media? Analysis of JUUL Twitter Followers� Age (Preprint)

2018 ◽  
Author(s):  
Annice Kim ◽  
Robert Chew ◽  
Michael Wenger ◽  
Margaret Cress ◽  
Thomas Bukowski ◽  
...  
Keyword(s):  
Social Media ◽  
Application Programming Interface ◽  
Media Analysis ◽  
Prediction Algorithm ◽  
Social Media Networks ◽  
Verification Methods ◽  
Twitter Account ◽  
Application Programming ◽  
Age Verification ◽  
Age Category

BACKGROUND JUUL is an electronic nicotine delivery system (ENDS) resembling a USB device that has become rapidly popular among youth. Recent studies suggest that social media may be contributing to its popularity. JUUL company claims their products are targeted for adult current smokers but recent surveillance suggests youth may be exposed to JUUL products online. To date, there has been little attention on restricting youth exposure to age restricted products on social media. OBJECTIVE The objective of this study was to utilize a computational age prediction algorithm to determine the extent to which underage youth are being exposed to JUUL’s marketing practices on Twitter. METHODS We examined all of @JUULvapor’s Twitter followers in April 2018. For followers with a public account, we obtained their metadata and last 200 tweets using the Twitter application programming interface. We ran a series of classification models to predict whether the account following @JUULvapor was an underage youth or an adult. RESULTS Out of 9,077 individuals following @JUULvapor Twitter account, a three-age category model predicted that 44.9% are 13 to 17 years old (N=4,078), 43.6% are 18 to 24 years old (N=3,957), and 11.5% are 25 years old or older (N=1,042); and a two-age category model predicted that 80.6% (N=7,313) are under 21 years old. CONCLUSIONS Despite a disclaimer that followers must be of legal age to purchase tobacco products, the majority of JUUL followers on Twitter are under age. This suggests that ENDS brands and social media networks need to implement more stringent age-verification methods to protect youth from age-restricted content.

Subjective Text Mining for Arabic Social Media

2017 ◽  
Vol 13 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Nourah F. Bin Hathlian ◽  
Alaaeldin M. Hafez
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Research Area ◽  
Arabic Text ◽  
Classification Methods ◽  
Learning Mechanisms ◽  
Subjective Analysis ◽  
Related Information ◽  
Data Source ◽  
Rich Content

The need for designing Arabic text mining systems for the use on social media posts is increasingly becoming a significant and attractive research area. It serves and enhances the knowledge needed in various domains. The main focus of this paper is to propose a novel framework combining sentiment analysis with subjective analysis on Arabic social media posts to determine whether people are interested or not interested in a defined subject. For those purposes, text classification methods—including preprocessing and machine learning mechanisms—are applied. Essentially, the performance of the framework is tested using Twitter as a data source, where possible volunteers on a certain subject are identified based on their posted tweets along with their subject-related information. Twitter is considered because of its popularity and its rich content from online microblogging services. The results obtained are very promising with an accuracy of 89%, thereby encouraging further research.

scholarly journals # Pillar of Defense: Using Social Media to Manage Impressions of Conflict: A Case Study of the November 2012 Israel-Hamas conflict

2021 ◽  
Author(s):  
Jelena Djurkic
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Impression Management ◽  
Armed Conflict ◽  
Character Structure ◽  
Military Involvement ◽  
Reputation Risk ◽  
Twitter Account ◽  
Israel Defense Forces

Threats to reputation can destroy a brand. Communicating effectively during a conflict can help to manage negative impressions that expose brands to reputation risk. This is important now more than ever as organizations—and nations—turn to Twitter to address various publics. The rigid 140-character structure of Twitter thus necessitates the creation of sound bites that act as productive texts to address multiple rhetorical objectives simultaneously. An examination of the Israel Defense Forces’ (IDF) Twitter account through sentiment and content analysis shows evidence that the Force took a significantly defensive approach to impression management of Operation Pillar of Defense in November 2012. There is evidence that Israel sought to re-frame public impression of its military involvement from aggressor to defender in the armed conflict. Codes discovered in the analysis suggest that the IDF tried to justify force, avoid responsibility and establish legitimacy of its operations.

scholarly journals Multi-Platform Social Media Use: Little Evidence of Impacts on Adult Well-Being

2020 ◽  
Author(s):  
Sophie Lohmann ◽  
Emilio Zagheni
Keyword(s):  
Social Media ◽  
Media Use ◽  
Scientific Evidence ◽  
General Social Survey ◽  
Well Being ◽  
Young Female ◽  
Social Media Use ◽  
Social Media Platforms ◽  
Data Source ◽  
Using Data

Social media have become a near-ubiquitous part of our lives. The growing concern that their use may alter our well-being has been met with elusive scientific evidence. Existing literature often simplifies social media use as a homogeneous process. In reality, social media use and functions vary widely depending on platform and demographic characteristics of users, and there may be qualitative differences between using few versus many different social media platforms. Using data from the General Social Survey, an underanalyzed data source for this purpose, we characterize intensive social media users and examine how differential platform use impacts well-being. We document substantial heterogeneity in the demography of users and show that intensive users tend to be young, female, more likely to be Black than Hispanic, from high SES backgrounds, from more religious backgrounds, and from families with migration background, compared to both non-users and moderate users. The intensity of social media use seemed largely unrelated to well-being in both unadjusted models and in propensity-score models that adjusted for selection bias and demographic factors. Among middle-aged and older adults, however, intensive social media use may be slightly associated with depressive symptoms. Our findings indicate that although mediums of communication have changed with the advent of social media, these new mediums are not necessarily detrimental to well-being.

scholarly journals Using social media data to map the areas most affected by ISIS in Syria

2020 ◽  
Vol 26 (1) ◽  
pp. 464-470
Author(s):  
Mohamad Hasan
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Geographical Information ◽  
Data Mapping ◽  
Islamic State ◽  
Social Media Data ◽  
The Social ◽  
Mapping Process ◽  
Data Source ◽  
Media Data

This paper presents a model to collect, save, geocode, and analyze social media data. The model is used to collect and process the social media data concerned with the ISIS terrorist group (the Islamic State in Iraq and Syria), and to map the areas in Syria most affected by ISIS accordingly to the social media data. Mapping process is assumed automated compilation of a density map for the geocoded tweets. Data mined from social media (e.g., Twitter and Facebook) is recognized as dynamic and easily accessible resources that can be used as a data source in spatial analysis and geographical information system. Social media data can be represented as a topic data and geocoding data basing on the text of the mined from social media and processed using Natural Language Processing (NLP) methods. NLP is a subdomain of artificial intelligence concerned with the programming computers to analyze natural human language and texts. NLP allows identifying words used as an initial data by developed geocoding algorithm. In this study, identifying the needed words using NLP was done using two corpora. First corpus contained the names of populated places in Syria. The second corpus was composed in result of statistical analysis of the number of tweets and picking the words that have a location meaning (i.e., schools, temples, etc.). After identifying the words, the algorithm used Google Maps geocoding API in order to obtain the coordinates for posts.

scholarly journals Social media supports tourism development in the COVID-19 normal era in Bandung

2021 ◽  
Vol 5 (3) ◽  
pp. 600-616
Author(s):  
Herpita Wahyuni ◽  
Eko Priyo Purnomo ◽  
Aqil Teguh Fathani
Keyword(s):  
Social Media ◽  
Tourism Development ◽  
Tourism Planning ◽  
New Era ◽  
Tourism Marketing ◽  
City Culture ◽  
Twitter Account ◽  
Use Of Social Media ◽  
Health Regulations

This research focuses on social media. We were using Social Media in Supporting Tourism Development During Covid-19: Case Study a New Era Policy in Bandung. This study uses descriptive qualitative research methods with data sources through the Twitter account of the Bandung City Culture and Tourism Office @DisbudparBdg assisted by the NVivo 12 Plus software. We are utilising Social Media to Support Tourism Development During Covid-19: A Case Study of New Era Policy in Bandung by measuring the use of social media in tourism planning, creation, integration, and marketing strategy. This research shows tourism planning in a new standard era by directing outdoor tourism and implementing health protocols. The Tourism Promotion Board integrates cooperation between the Bandung City Culture and Tourism Office and PT Kereta Api Pariwisata. Tourism marketing by providing tourist information can give tourists confidence that Bandung is an attractive and robust destination city in improving health regulations and strictly following health protocol rules during recreation.

scholarly journals Exploring public engagement with missing person appeals on Twitter

2020 ◽  
Author(s):  
Reka Solymosi ◽  
Oana Petcu ◽  
Jack Wilkinson
Keyword(s):  
Social Media ◽  
Public Engagement ◽  
Evidence Base ◽  
Evidence Based ◽  
The Public ◽  
Missing Persons ◽  
Early Return ◽  
Police Agencies ◽  
Key Factor ◽  
Twitter Account

Police agencies globally are seeing an increase in reports of people going missing. These people are often vulnerable, and their safe and early return is a key factor in preventing them from coming to serious harm. One approach to quickly find missing people is to disseminate appeals for information using social media. Yet despite the popularity of twitter-based missing person appeals, presently little is known about how to best construct these messages to ensure they are shared far and wide. This paper aims to build an evidence-base for understanding how police accounts tweet appeals for information about missing persons, and how the public engage with these tweets by sharing them. We analyse 1,008 Tweets made by Greater Manchester Police between the period of 2011 and 2018 in order to investigate what features of the tweet, the twitter account, and the missing person are associated with levels of retweeting. We find that tweets with different choice of image, wording, sentiment, and hashtags vary in how much they are retweeted. Tweets that use custody images have lower retweets than Tweets with regular photos, while tweets asking the question “have you seen...?” and asking explicitly to be retweeted have more engagement in the form of retweets. These results highlight the need for conscientious, evidence-based crafting of missing appeals, and pave the way for further research into the causal mechanisms behind what affects engagement, to develop guidance for police forces worldwide.

scholarly journals PENERAPAN TEXT MINING UNTUK MELAKUKAN CLUSTERING DATA TWEET AKUN BLIBLI PADA MEDIA SOSIAL TWITTER MENGGUNAKAN K-MEANS CLUSTERING

2022 ◽  
Vol 10 (4) ◽  
pp. 583-593
Author(s):  
Syiva Multi Fani ◽  
Rukun Santoso ◽  
Suparti Suparti
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Virtual Networks ◽  
Number Of Clusters ◽  
Silhouette Coefficient ◽  
Twitter Account ◽  
Computer Based ◽  
Twitter Users ◽  
Clustering Data ◽  
Coefficient Method

Social media is computer-based technology that facilitates the sharing of ideas, thoughts, and information through the building of virtual networks and communities. Twitter is one of the most popular social media in Indonesia which has 78 million users. Businesses rely heavily on Twitter for advertising. Businesses can use these types of tweet content as a means of advertising to Twitter users by Knowing the types of tweet content that are mostly retweeted by their followers . In this study, the application of Text Mining to perform clustering using the K-means clustering method with the best number of clusters obtained from the Silhouette Coefficient method on the @bliblidotcom Twitter tweet data to determine the types of tweet content that are mostly retweeted by @bliblidotcom followers. Tweets with the most retweets and favorites are discount offers and flash sales, so Blibli Indonesia could use this kind of tweet to conduct advertising on social media Twitter because the prize quiz tweets are liked by the @bliblidotcom Twitter account followers.

scholarly journals Student Writen Conversation In The Midst Of Social Media Era

2020 ◽  
Vol 5 (1) ◽  
pp. 12-18
Author(s):  
Eko Kuntarto
Keyword(s):  
Social Media ◽  
Focus Group ◽  
Positive Attitude ◽  
Negative Impact ◽  
Group Discussion ◽  
Real Life ◽  
Real Relationship ◽  
The Social ◽  
Data Source ◽  
Oral Interaction

This research aimed to explain the model of writen conversationin the social media era, such presence of WhatsApp (WA) as well as to explore some of the positive contributions of WA used in building the Real Life Communication. By applying the Exploratory design, this research involved 4 participants as a purposively selected data source with indicators as WA users. Data were collected through Focus Group Discussion, Interview, and Observation and analyzed by several stages i.e. data reduction, displaying data, categorizing, and verifying and concluding. The results showed that Indonesia writen conversationcan decrease as the dominant use of WA was not wise. Nevertheless, the use of WA applications also had some positive contributions in building a real relationship. Finally, the assumption that the negative impact of using the WA application should be able to change the mindset and positive attitude in initiating and defending an oral interaction.

Sign in / Sign up

Export Citation Format

Share Document