Social Networking Site Twitter Research Articles

The Relationship between "Zero Waste" and Food: Insights from Social Media Trends.

Zero waste (ZW), the concept of reducing waste production, is now becoming a lifestyle trend. Social media is strengthening this by popularizing the movement and connecting related communities. ZW and food are closely related, since food waste is a significant sustainability issue; however, the exact relationship between ZW and food communication on social networks is not clear. This study analyzed user communication on the social networking site Twitter between July 2008 and April 2023 to determine how members communicated and shared topics related to ZW and food; an analysis of hashtag frequency was also conducted. During the study period, a total of 50,650 tweets with both #zerowaste and #food hashtags were recorded, written by 21,271 unique users from all over the world. Topic analysis identified the nine related topics: ZW lifestyle, leftover recipes, ZW events, food rescue, climate change, packaging, ZW stores, composting, and ZW restaurants; visual analysis indicated that these topics were closely connected, suggesting common membership of these communities. Overall, our results provide insight into the ZW and food communities on Twitter, which may be useful for marketers, influencers, and government agencies to create targeted content and facilitate wider adoption of a ZW lifestyle.

Comparing the Performance of Data Mining Algorithms in Predicting Sentiments on Twitter

On Twitter, users can post tweets, videos, and images. It can, however, also be disruptive and difficult. To categorize the material and improve searchability, hashtags are crucial. This study focuses on examining the opinions of Twitter users who participate in trending topics. The algorithms K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are used for sentiment analysis. The data set comprises tweet information on popular topics that was collected using the Twitter API and saved in Excel format. SVM and K-NN are used for data preparation, weighting, and sentiment analysis. With 105 data points, the study provides insight into user sentiment. SVM identified 99% of positive responses and 1% of negative responses with an accuracy of 80%. KNN successfully identified 90% of the positive responses and 10% of the negative responses, with an accuracy rate of 71.4%. According to the results, SVM performs better when analyzing the sentiment of hashtag users on Twitter.

Sentiment Analysis of Public Acceptance of Covid-19 Vaccines Types in Indonesia using Naïve Bayes, Support Vector Machine, and Long Short-Term Memory (LSTM)

The Covid-19 vaccination is a government program during the pandemic to create herd immunity so that people become more productive in their activities. In Indonesia, the Covid-19 vaccination campaign employs a range of vaccines and has sparked a range of responses from the public on social media, particularly Twitter. Users can tweet and communicate with one another on the social networking site Twitter. This study uses a Sentiment Analysis technique using the Nave Bayes (NB), Support Vector Machine (SVM), and Long Short-Term Memory (LSTM) algorithms to conduct a sentiment analysis of public acceptance of the type of Covid-19 vaccine used in Indonesia using Twitter data. Various types of vaccines in Indonesia include Sinovac, Vaksin Covid-19 Bio Farma, AstraZeneca, Pfizer, Moderna, Sinopharm, Novavax, Sputnik-V, Janssen, Convidencia, Zifivax, often confuse the public in determining the objectivity of this opinion. In addition, theoretically, this study also seeks to contrast the NB, SVM, and LSTM algorithms with experimental techniques to obtain the best algorithm model. The stages of the research involved gathering information based on Twitter user opinions about the type of Covid-19 vaccine on Twitter from January 2021 to January 2022. The researcher used Indonesian language tweet data with the keywords #vaksincorona, #vaksincovid19, #vaksinasi, #ayovaksin, #lawancovid19, and #vaksinindonesia. Before modelling, the pre-processing stage consists of case folding, tokenizing, filtering, stemming, and word weighting using TF-IDF. After that, model testing was carried out using Cross Validation with the Python programming language, and evaluation and validation of the test results using the Confusion Matrix. The results showed that the accuracy score of the SVM method for the best model was 84.89%, while for the Naïve Bayes and LSTM algorithms, they were 84.65% and 82.97%, respectively.

K-Nearest Neighbor and Naive Bayes Classifier Methods for Expedition Service Comparison Analysis of User Sentiments


 
 
 
 Depending on the service chosen, expedition is one of the freight forwarding companies that operate in the domestic market. The availability of expedition services can make it easier for traders to transfer items to purchasers who conduct online transactions, as well as encourage shipping businesses to collaborate with online dealers. The JNE, JNT, and Pos Indonesia excursions were utilized in this study. The goal of this project is to develop an analytical model that will make it simpler for online merchants to find collaborators for effectively and securely transporting their goods. Based on user sentiment on the social networking site Twitter, this study uses sentiment analysis. With the keywords "JNT, JNE, and Pos Indonesia," this study compares the accuracy results using the Naive Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms. According to this study, testing accuracy for the NBC method was 80% and training accuracy was 83%. While the accuracy of the KNN approach is 68%. According to public opinion, the JNE expedition is the best one for distributing products, scoring 68.58% in favor of it and 30.64% against it.
 
 
 
 

Recurrent neural network based sentiment analysis of social media data during corona pandemic under national lockdown

The Corona virus pandemic has affected the normal course of life. People all over the world take the social media to express their opinions and general emotions regarding this phenomenon. In a relatively short period of time, tweets about the new Corona virus increased by an amount never before seen on the social networking site Twitter. In this research work, Sentiment Analysis of Social Media Data to Identify the Feelings of Indians during Corona Pandemic under National Lockdown using recurrent neural network is proposed. The proposed method is analyzed using four steps: that is Data collection, data preparation, Building sentiment analysis model and Visualization of the results. For Data collection, the twitter dataset are collected from social networking platform twitter by application programming interface. For Data preparation, the input data set are pre-processed for removing URL links, removing unnecessary spaces, removing punctuations and numbers. After data cleaning or preprocessing entire particular characters and non-US characters from Standard Code for Information Interchange, apart from hash tag, are extracted as refined tweet text. In addition, entire behaviors less than three alphabets are not assumed at analysis of tweets, lastly, tokenization and derivation was carried out by Porter Stemmer to perform opinion mining. To authenticate the method, categorized the tweets linked to COVID-19 national lockdown. For categorization, recurrent neural method is used. RNN classify the sentiment classification as positive, negative and neutral sentiment scores. The efficiency of the proposed RNN based Sentimental analysis classification of COVID-19 is assessed various performances by evaluation metrics, like sensitivity, precision, recall, f-measure, specificity and accuracy. The proposed method attains 24.51%, 25.35%, 31.45% and 24.53% high accuracy, 43.51%, 52.35%, 21.45% and 28.53% high sensitivity than the existing methods.

Mega Mergers in the Seeds & Agro-chem Industry

The Seeds and Agro-Chem Industry today is a tightly knit oligopoly with only a handful of global players. Following a detailed assessment, the European Commission recently conditionally cleared three major transactions in the already highly concentrated sector - Chem China and Syngenta, Dow and Du Pont, Bayer and Monsanto – reducing the number of effective global players from six-to-four. Even though the Commission’s decisions are laudatory in terms of their economic assessment of the impact of the transactions on product, price and innovation competition, these merger approvals suggest the following gap in EU Merger Control. Taking pride in its more economic approach, the EU Merger Control in its current form neglects the need to integrate the most fundamental principles of EU law. These principles can neither be easily quantified nor put in a straitjacket of ‘cost/benefit’ or ‘efficiency’ analysis. This article accordingly calls for the need to go back to the Treaty articles and examine how EU Merger Control can effectively meet the larger policy objectives as enshrined in the Treaty articles, such as Article 11 TFEU’s ‘environmental integration rule’, while simultaneously retaining the impression of being based in sound principles of competition law and economics. Incorporation of the principle of sustainable development alongside the well-defined economic principles well aligns with an integrated and holistic approach to policy-making. The approach suggested may lead to a multiciplty of objectives – meaning that if such an approach is indeed adopted, the EU Merger Control may well need to look beyond the narrow construct of ‘efficiency’ and ‘consumer welfare’. A failure to take account of these larger objectives, however, may ironically thwart the EU Merger Control from achieving the very fundamental objective it seemingly aspires to achieve that is ‘consumer welfare’! Consumers being numerous and geographically dispersed experience the collective action problem. In the Bayer/Monsanto merger, despite this typical collective active problem, the Commission received over 55,000 emails, letters and postcards and an uncountable number of tweets on the social networking site Twitter. The citizens, who are also consumers, in their complaints requested the Commission to prohibit the transaction, as they saw the proposed merger being detrimental to ‘human health, food safety, consumer protection, the environment and the climate’. The Commission’s response to these complaints was that even though the said concerns were significant - they nonetheless could not form the basis of merger assessment, which needs to be limited to competition issues. As for the issues raised, in the opinion of the Commission, other areas of law such as those dealing with the regulatory system for pesticides and the consumer protection law could well address these other concerns. The dilemma confronting the Commission was whether to assess these transactions within the current framework grounded in well-defined scientific principles of economics (and increasingly econometrics) or in the alternative take account of some qualitative non-price considerations. The Commission evidently resorted to the former option. A decision otherwise would have been subject to intense economic criticism just like the GE/Honeywell decision, wherein the Commission proposed a very novel theory of ‘Archimedean Leveraging’, and prohibited the proposed merger. This means that for a truly effective competition policy and EU Merger Control in particular, the authorities need to ‘re-think, re-design and re-frame’ the notion of competition policy as a ‘system of inter-locking processes’ in the Raworth’s ‘doughnut’. For such a sustainability-driven thinking on innovation, that re-directs the ‘consumption choices available to consumers’ within the sustainable ‘safe and just space for humanity’, there is a visible need to think and reflect upon the ‘double limit of planetary boundaries’ and incorporate it in the everyday philosophy of competition policy.
 

Hate Speech Hashtag Classification Using Hybrid Artificial Neural Network (ANN) Method

Social networking sites Twitter is frequently used as a platform for information gathering various communities/forums as well as individuals to discuss certain things. Dissemination of information on Twitter can be in the form of positive information and negative information. One of the negative information is hate speech contained in the form of hashtags on twitter. Hate Speech Hashtag Classification was be carried out using the Hybrid Artificial Neural Network (ANN) method to produce satisfactory results compared to previous methods such as KNN and so on because the large amount of data in Twitter will be very profitable and produce good accuracy when using Hybrid Learning, Hybrid Learning with 5 Cross Validation the highest accuracy is 79% , the lowest is 73%, the average accuracy is 76%.

Vaccine Hesitancy and Administrative Burden in the Australian National Immunisation Program: An Analysis of Twitter Discourse

In Australia, the National Immunisation Program and its Standard Vaccination Schedule are administered by the Australian Government Department of Health. While the public vaccination program’s safety and worth are generally agreed upon by doctors and public health professionals, some continue to see vaccinations as a source of danger and harm. The burden of vaccination in order to receive public services aligns government and medical interests, but a less-than-trusting public may see conspiracy in such requirements, resulting in vaccine hesitancy. The media’s attention to the topic, and a tendency toward misinformation on the part of anti-government opinion leaders, necessitate additional exploration of the administrative burden of vaccinations in an increasingly complex policy environment, where public health benefits are weighed against individual freedom and belief. This paper examines vaccinations as a burden, with costs in compliance, learning, and psychological terms, using posts from the social networking site Twitter as a corpus for exploratory content analysis in the specific case of Australia and its requirements. It is worth considering whether the positive aspects messaged by public health professionals are successfully entering into the discourse on vaccinations.

Narcissism and Social Media: The Role of Communal Narcissism.

Agentic narcissism and vulnerable narcissism have been widely studied in relation to social media use. However, with research on communal narcissism in its early stages, the current study examines communal narcissism in relation to social media use. Specifically, the current study investigates whether communal narcissism is related to use and frequency of use of the popular social networking sites Instagram, Reddit and Twitter, and if communal narcissism relates to the importance of receiving feedback and to the quality-rating of self-presented content on those platforms. A total of 334 individuals were recruited from Amazon Mechanical Turk, with two-thirds being male (66.7%). A regression analysis showed that communal narcissism was related to increased use of Instagram and Twitter but not Reddit. Sharing content, the importance of feedback and better than average ratings had positive associations with communal narcissism. The relationship between communal narcissism and sharing on social media was fully mediated by wanting validation on social media and higher ratings of self-presented content. Communal narcissism had a notably strong relationship with wanting validation on all platforms and our results suggest that communal narcissism might be especially relevant in the context of social media use.

'IT'S 1776, BABY!': BROADCASTING REVOLUTIONARY PERFORMANCE DURING THE U.S. CAPITOL RIOTS

This presentation focuses on the documentation and mediation of the January 6, 2021 breach of the U.S. Capitol by supporters of then-President Donald Trump in an effort to overturn the certification of Joseph Biden’s electoral victory. We analyzed videos participants recorded and shared through a variety of social networking, live-streaming, and messaging applications. We offer a cross-platform descriptive analysis of footage transmitted from participants during the Capitol Riots from seven different platforms: the social networking sites Facebook, Twitter, and Parler; the live-streaming sites DLive, Twitch, and Periscope; and the messaging application Snapchat. In examining this range of platforms and applications, we argue not just for the importance of attending to the documentation of violent protests, but to also account for the broad spectrum of possibilities at play across the ecology of digital video-sharing platforms in building digitally networked publics. This analysis allows us to provisionally argue that the Capitol Rioters were not only interested in particular political outcomes; they were also interested in mediated outcomes that were consciously drawing from the structured affordances of their smartphones and their online networks to create many different media spectacles that were distributed across an ecology of platforms.

Twitter Sentiment Analysis towards COVID-19 Vaccines in the Philippines Using Naïve Bayes

A year into the COVID-19 pandemic and one of the longest recorded lockdowns in the world, the Philippines received its first delivery of COVID-19 vaccines on 1 March 2021 through WHO’s COVAX initiative. A month into inoculation of all frontline health professionals and other priority groups, the authors of this study gathered data on the sentiment of Filipinos regarding the Philippine government’s efforts using the social networking site Twitter. Natural language processing techniques were applied to understand the general sentiment, which can help the government in analyzing their response. The sentiments were annotated and trained using the Naïve Bayes model to classify English and Filipino language tweets into positive, neutral, and negative polarities through the RapidMiner data science software. The results yielded an 81.77% accuracy, which outweighs the accuracy of recent sentiment analysis studies using Twitter data from the Philippines.

The transnational discourse of political protests: setting the agenda through social media

This article analyses the role of social media as a transnational discursive space and the impact of networked communication on the formation of the traditional mass media agenda regarding political protests that began in June 2019 in Hong Kong. The aim of the present research was to indicate the degree of impact of the dominant themes in networked communication during the anti-extradition bill protests in the transnational network discourse and the impact on the news media agenda, taking into account the activity of user-generated network traffic around the published content. The research was based on two theories shaping the perception of political protests in an international context - theory on transnational discursive spaces and theories of agenda setting. The research was carried out using quantitative content analysis and confirmed that global social networking sites Facebook and Twitter are important channels in creating transnational discursive spaces that affect the news media's agenda. Findings show that social media plays an important role in organizing political protests, and is a tool for establishing transnational discursive spaces; despite the fact that the protesters used applications protecting their data for communication, with the assistance of information and integrated collaboration by other entities. The results obtained contribute to the research on media studies which highlight the role and importance of social media in the process of communicating about political protests.

‘Şule Çet İçin Adalet’: Twitter Verisinin Eleştirel Söylem Çözümlemesi Modeli ile İncelenmesi

Kadın cinayetleri sadece Türkiye’de değil dünya çapında çözülmeyi bekleyen önemli bir sorundur. Kadın cinayetleri femicide kavramının Türkçe alanyazın içerisinde kullanılan en yaygın tanımıdır. Kadın cinayeti denildiğinde en basit anlamda kadının sadece kadın olduğu için öldürülmesinin ifadesidir. Bu çalışmada Şule Çet cinayeti ardından mikro-blog olan sosyal paylaşım sitesi Twitter verilerinin geriye dönük olarak taranması ve eleştirel söylem çözümlemesi ile araştırılmasını kapsamaktadır. Şule çet için adalet hastag’i ile oluşturulan mikro-bloğun incelenmesi ve analizleri sonucunda elde edilen bulgular arasında Türkiye’deki adelet sisteminin eril bir adalet olduğu, kadınların cinsel hayatlarının, bekar ve çalışıyor olmalarının, ailelerinde uzak yaşıyor olmalarının, giyim tarzlarının tecavüzü ve cinayeti meşrulaştıran kavramlar olarak görüldüğü sonuçlarına ulaşılmıştır. Yapılan incelemeler sonucunda geçtiğimiz yıllarda yine Türkiye’de işlenen tecavüz ve cinayetlere göndermeler yapılmış ve adaletin sağlanması için çağrılar yapılmıştır. Ayrıca ayrıcalıklı gruplara uygulanan cinsel tacizler de kınanmıştır.

السیاسة الخارجیة کما تعرض لها الحسابات الرسمیة السعودیة عبر موقع التواصل الاجتماعی تویتر: دراسة تحلیلیة

مع ظهور وسائل وأدوات «الاتصال»، وثورة تکنولوجيا المعلوماتية، وما أحدثته من تغيرات متلاحقة وسريعة في مجال الاتصال، وقدرتها على ربط العالم دولا وشعوبا وحکومات، أصبح تشکيل العلاقات طويلة المدى بين المملکة والمجتمع الدولي في حاجة إلى فهم لمتطلبات ودوافع وحاجات الأداء الذي يتم في نسق واع ومنظم، ومن خلال عمليات واعية ومنظمة، توظف جهود «المواطنين»، إضافة إلى مبادراتهم «الفردية» والإبداعية، وجهودهم «الابتکارية» في استخدام وسائل الاتصال وأنواعه، وتسخير کل ذلک في بناء صور ذهنية جديدة لما يحدث في المملکة، وتوظيف هذه الصور الجديدة في نشر ثقافة المملکة، وقيمها، وإبراز التجليات المختلفة لقوتها الناعمة، والتأثير على صناعة توجهات جديدة «حقيقية»، وتصويب اتجاهات الرأي العام إقليميا وعالميا فيما يتعلق بکل ما تم ترسيخه في الأذهان من قبل الجهات الکارهة أو المعادية للمملکة. في ضوء ذلک کله تکمن المشکلة البحثية الحالية في التساؤل الرئيس التالي: ما الصورة التي تمارس من خلالها السياسة الخارجية للمملکة العربية السعودية کما يعکسها الحساب الرسمي لوزارة الخارجية السعودية على موقع التواصل الاجتماعي (تويتر)؟، وما تأثير توجهات المملکة نحو مختلف القوى السياسية الفاعلة على المستوى الإقليمي أو الدولي على محتوى ما يعرضه الحساب الرسمي لوزارة الخارجية السعودية عبر موقع التواصل الاجتماعي تويتر؟ Saudi's foreign policy in Twitter's official accounts: an analytical study With the emergence of means and tools of the revolution in information technology, and the successive and rapid changes that it has brought about in the field of communication, and its ability to connect the world with countries, peoples, and governments, the formation of long-term relations between the Kingdom and the international community has become in need of an understanding of the requirements, motives, and needs of the performance that takes place in A conscious and organized coordination, and through conscious and organized processes, that employ the efforts of citizens, in addition to their individual and creative initiatives, and their innovative efforts in using the means and types of communication, and harnessing all this to build new mental of what is happening in the Kingdom, and employing these new images in spreading the Kingdom's culture and values, highlighting the various manifestations of its soft power, influencing the manufacture of new real trends, and correcting public opinion trends regionally and globally concerning everything that has been entrenched in the minds of those who hate or hostile to the Kingdom. In light of all this, the current research problem lies in the following central question: What is the image in which the foreign policy of the Kingdom of Saudi Arabia is practiced as reflected in the official account of the Saudi Ministry of Foreign Affairs on the social networking site (Twitter), and what is the impact of the Kingdom's attitudes towards the various political forces at the level Regional or international, for the content presented by the official account of the Saudi Ministry of Foreign Affairs via the social networking site Twitter.

Üretüketici Emeğin Metalaşması: Twitter Örneğinde Eleştirel Ekonomi Politik Bir Çözümleme

Dealing with the commodification processes and exploitation of users who participate in online activities on the social networking site Twitter, this study is based on the critical political economy approach. In this study, in which the rise of social media along with the recent developments in communication technologies was evaluated within the capitalist modes of production and style, the production and consumption relations observed in Twitter were examined. The capitalist relations, processes and forms dominating Twitter have evaluated under the thematic categories of analysis; the determinations made in these categories were obtained from semi-structured in-depth interviews conducted with the chosen research group of 10 participants, by intended sampling technique among Twitter users. It is concluded that Twitter is seen by the participants as a digital space in which production and exchange relations take place and a tool that enables these relations to be actualised.

The “Fansumer” Phenomena in the Korean Pop Culture Industry: The Produce X 101 Vote Rigging Scandal

현재의 소비 트렌드는 뉴미디어 기술 발달의 영향으로 인해 집단 지성을 통한 소비자 행동주의를 실현하게 된 ‘팬슈머’의 형태로 진화하였고, 이에 소비자는 선발과 양육, 기획과 제조, 유통과 홍비, 지지와 비판까지 기존의 수동적 입장에서 능동적이고 적극적인 입장으로 변화하였다. 특히 팬층의 영향력을 기반으로 운영 및 유지되는 연예산업에서는 변화된 소비 트렌드에 의해 팬덤이 팬슈머로서 변화하며 다양한 형태들을 통해 그 영향력을 키우게 되었다. 이에 한국 대중문화산업에 나타난 팬슈머 현상을 모색하기 위해 <프로듀스 X 101> 투표 조작 사건에 나타난 팬슈머 현상의 특징과 구체적인 사항을 분석하였다. 그 결과 첫째, 팬슈머는 집단 지성을 기반으로 소비자 행동주의를 실천한다는 것. 둘째, 그 집단 지성은 접근성이 용이한 소셜네트워크서비스 ‘트위터’를 기반으로 집단 행동을 보인다는 것. 셋째, 온라인과 오프라인의 경계를 넘어 능동적이고 적극적인 행동주의를 실천한다는 것. 넷째, 지역적 제한과 지역적 특성을 넘어 전 세계적인 문화 현상으로서 나타난다는 것으로 정리할 수 있었다.A current consumption trend has evolved into the form of a “fansumer”, which has led to the realization of consumer activism through collective intelligence owing to the influence of new media technology development. Consumers have shifted from the existing passive stance to an active positions, which covers a wide range of consumer habits and behavior, including selection and nurturing, planning and manufacturing, distribution and promotion, and support and criticism. In the entertainment industry, which operates based on the influence of fanbases, fandom has been transformed into fansumers through changing consumption trends and its influence thereof. To shed light on the fansumer phenomenon in the Korean pop culture industry, we analyzed the characteristics and details of this phenomenon in the Produce X 101 vote rigging scandal. The results were as follows. First, fansumers were found to practice consumer activism based on collective intelligence. Second, collective intelligence led to collective action based on the social networking site Twitter, which is easy to access. Third, fansumer activism goes beyond the boundaries of online and offline practices. Fourth, the fansumer phenomenon could be summarized as a global cultural phenomenon beyond regional restrictions and characteristics.

The Increasing Interest in Antibiotic Stewardship Programs

Background: The inappropriate use of antibiotics leads to many adverse effects and also leads to bacterial resistance. A hospital-based program, commonly referred to as antibiotic stewardship programs, is used to improve the usage of antibiotics. This study aims to explore the increasing interest of the public in antibiotic stewardship programs by using data from Google Trends and Twitter.&#x0D; Methodology: A search trends feature that shows how frequently a given search term is entered into Google’s search engine (Google Trends) and a social network site (Twitter) were used.&#x0D; Results: The public and the health care professionals are now more interested in antibiotic use and antibiotic resistance due to the development of more severe infections that were caused by bacteria resisted to many antibiotics which lead to high morbidity and mortality rates.&#x0D; Conclusion: There is a high prevalence of infections caused by multi-drug resistant organism that could lead to more mortality and morbidity rates, as a result the interest in antimicrobial stewardship programs in internet is increased. So it is important to increase the knowledge of health care professionals regarding the appropriate antibiotic use and to encourage them to change their unsuitable prescribing patterns.

Opinião e cenários comunicativos: influência de fatores contextuais nos processos sociopsicológicos da espiral do silêncio

Este artigo tem como objetivo investigar como fatores contextuais podem afetar os processos sociopsicológicos especificados pela teoria da espiral do silêncio, como o medo de isolamento e a congruência de opinião. Os contextos para este artigo foram divididos em ambientes on-line – sites de redes sociais, salas de bate-papo e fóruns de discussão on-line – e comunicação face a face. Os dados foram obtidos a partir da aplicação de questionários on-line sobre a opinião a respeito da união civil entre pessoas do mesmo sexo. Com um total de 226 formulários preenchidos, os dados coletados receberam tratamento estatístico para a realização do teste das hipóteses. A análise dos dados demonstrou que a expressão da opinião está ligada a fatores que se relacionam com as características específicas de cada meio/ambiente em que a opinião é expressa, em conjunto com os fatores sociopsicológicos que operam na espiral do silêncio. Ou seja, a configuração da comunicação afeta o desejo dos indivíduos em expressar seus pontos de vista, fazendo com que a espiral do silêncio aconteça de forma diferente em cada contexto específico.

The use of Twitter and Youglish for the learning and retention of commonly mispronounced English words

Although there is an increasing interest in educational microblogging and findings regarding its effectiveness on the language learning, relevant research, especially on the use of microblogging for the learning of pronunciation, is rather limited. This issue becomes even more apparent in countries like Turkey where English is taught as a foreign language and there is considerable number of words commonly mispronounced by Turkish language learners including pre-service language teachers. The present paper reports on the findings of a study into the effects of the social networking site Twitter and Youglish on the learning and retention of commonly mispronounced words. Twitter, a microblogging tool, was used for explicit instruction and input enhancement for the words by capitalizing of stressed syllables, providing links to authentic talks, stressing the problematic features of the target words, and showing other pronunciation-related familiar words. Youglish was used to utilize the tenets of extensive listening and input enhancement. Tweets aimed at drawing direct attention to the pronunciation of each word. In each tweet, a link to Youglish was provided as an attempt to foster pronunciation learning in context. Additionally, this study examines the attitudes towards pronunciation and views on the use of Twitter and Youglish for pronunciation instruction. Following an experimental group only design (pre, post, and retention tests), the study was conducted with 93 pre-service teachers studying at the English Language Teacher Education (ELTE) program of a large-scale university in Turkey. The data were gathered via a Pronunciation Attitude Inventory, a pronunciation test, and an open-ended survey. Seventy target words were determined after a four-week observation and note taking of commonly mispronounced words by teacher trainers and these target words were sent in 70 tweets, one word in each tweet. The tweets for each word included a link to Youglish, a Youtube-based pronunciation dictionary. Descriptive statistics and ANOVA tests were run for the analysis of the quantitative data and content analysis for the open-ended survey. The results indicated that the use of Twitter and Youglish together to teach pronunciation served an important role in learning and retaining commonly mispronounced words. The views of the pre-service teachers support the findings that they benefitted from the adopted approach. Findings from this study have strengthened the evidence supporting the impact of Twitter (supported by Youglish) for pronunciation instruction. The study also offers implications for leaners, teachers, and policy makers.

Hashtag Unity: Qatar’s digital nationalism in the Gulf crisis

This article examines digital expressions of solidarity and unity that emerged on social media platforms in Qatar following the outbreak of the Gulf crisis in June 2017. The study undertakes an analysis of public tweets on the social network site Twitter published around Arabic hashtags in Twitter’s Qatar trends in the first two weeks of the blockade. The hashtags attracted thousands of users to form a digitally connected public calling for national unity and solidarity. An qualitative analysis of a sample from 402,962 tweets published around these hashtags reveals that users expressed national unity and solidarity through both visual and textual displays of strength, resilience, loyalty and pride. The article argues that following their emergence, the hashtags not only aimed to cement resistance against the blockade imposed on Qatar but also to forge a national identity that was centred on the persona of the nation’s leader, Sheikh Tamim Al-Thani, while denouncing social and cultural divisions that stemmed from transnational tribal identities.