Languages, Code-Switching Practice and Primary Functions of Facebook among University Students

The purpose of this study was to determine the languages used in Facebook wall posts and comments, code-switching practice of these multilingual university students and functional orientation of their Facebook wall posts and comments. This study was mainly based on the investigation of the latest 50 Facebook comments of 100 Malay public university students in Malaysia. The first language of these university students is Bahasa Malaysia and English is their second language. The content analysis of wall posts was used to analyze the code-switching language used in the Facebook and the primary functions of the Facebook comments by categorizing them using Thurlow’s (2003) SMS categories that contain nine orientations. The findings indicate that majority of the Facebook users comments are categorized under friendship maintenance orientation to maintain existing relationships and create new friendships. The findings indicate heavily abbreviated languages in English and Bahasa Malaysia. It is found that situational code-switching between English and Bahasa Malaysia is heavily utilized by multi-lingual Facebook users. The research is significant in a number of ways as it offers the communication culture of Facebook among public university students in Malaysia. In addition, the study indicates that Social Network Sites can also be a potential teaching and learning tool to teach English since learners nowadays are members of various Social Network Sites

Sentiment Analysis of Afaan Oromoo Facebook Media Using Deep Learning Approach

The rapid development and popularity of social media and social networks provide people with unprecedented opportunities to express and share their thoughts, views, opinions and feelings about almost anything through their personal webpages and blogs or using social network sites like Facebook, Twitter, and Blogger.  This study focuses on sentiment analysis of social media content because automatically identifying and classifying opinions from social media posts can provide significant economic values and social benefits. The major problem with sentiment analysis of social media posts is that it is extremely vast, fragmented, unorganized and unstructured. Nevertheless, many organizations and individuals are highly interested to know what other peoples are thinking or feeling about their services and products. Therefore, sentiment analysis has increasingly become a major area of research interest in the field of Natural Language Processing and Text Mining. In general, sentiment analysis is the process of automatically identifying and categorizing opinions in order to determine whether the writer's attitude towards a particular entity is positive or negative. To the best of the researcher’s knowledge, there is no Deep learning approach done for Afaan Oromoo Sentiment analysis to identify the opinion of the people on social media content. Therefore, in this study, we focused on investigating Convolutional Neural Network and Long Short Term Memory deep learning approaches for the development of sentiment analysis of Afaan Oromoo social media content such as Facebook posts comments. To this end, a total of 1452 comments collected from the official site of the Facebook page of Oromo Democratic Party/ODP for the study. After collecting the data, manual annotation is undertaken. Preprocessing, normalization, tokenization, stop word removal of the sentence are performed. We used the Keras deep learning python library to implement both deep learning algorithms. Long Short Term Memory and Convolutional Neural Network, we used word embedding as a feature. We conducted our experiment on the selected classifiers. For classifiers, we used 80% training and 20% testing rule. According to the experiment, the result shows that Convolutional Neural Network achieves the accuracy of 89%. The Long Short Memory achieves accuracy of 87.6%. Even though the result is promising there are still challenges. Keywords: Sentiment Analysis; Opinionated Afaan Oromoo facebook comments; Oromo Democratic Party Facebook page DOI: 10.7176/NMMC/90-02 Publication date:May 31st 202

Determining citizens’ opinions about stories in the news media: analysing Google, Facebook and Twitter

We describe a method whereby a governmental policy maker can discover citizens’ reaction to news stories. This is particularly relevant in the political world, where governments’ policy statements are reported by the news media and discussed by citizens. The work here addresses two main questions: whereabouts are citizens discussing a news story, and what are they saying? Our strategy to answer the first question is to find news articles pertaining to the policy statements, then perform internet searches for references to the news articles’ headlines and URLs. We have created a software tool that schedules repeating Google searches for the news articles and collects the results in a database, enabling the user to aggregate and analyse them to produce ranked tables of sites that reference the news articles. Using data mining techniques we can analyse data so that resultant ranking reflects an overall aggregate score, taking into account multiple datasets, and this shows the most relevant places on the internet where the story is discussed. To answer the second question, we introduce the WeGov toolbox as a tool for analysing citizens’ comments and behaviour pertaining to news stories. We first use the tool for identifying social network discussions, using different strategies for Facebook and Twitter. We apply different analysis components to analyse the data to distil the essence of the social network users’ comments, to determine influential users and identify important comments

FRAppE: Detecting Malicious Facebook Applications

Online social media services like Facebook witness an exponential increase in user activity when an event takes place in the real world. This activity is a combination of good quality content like information, personal views, opinions, comments, as well as poor quality content like rumours, spam, and other malicious content. Even if the good quality content makes online social media very good source of information, uses of bad quality content can degrade user experience, and could have an inappropriate impact in the real world. It could also impact the enormous promptness, promptness, and reach of online social media services across the globe makes it very important to monitor these activities, and minimize the production and spread of bad quality content. Multiple studies in the past have analysed the content spread on social networks during real world events. However, little work has explored the Facebook social network. Two of the main reasons for the lack of studies on Facebook are the strict privacy settings, and limited amount of data available from Facebook, as compared to Twitter. With over 1 billion monthly active users, Facebook is about times bigger than its next biggest counterpart Twitter, and is currently, the largest online social network in the world. In this literature survey, we review the existing research work done on Facebook, and study the techniques used to identify and analyse poor quality content on Facebook, and other social networks. We also attempt to understand the limitations posed by Facebook in terms of availability of data for collection, and analysis, and try to understand if existing techniques can be used to identify and study poor quality content on Facebook

Kako gradonačelnici u zemljama srednje i jugoistočne Europe koriste Facebook

The ever increasing rise of social media network users consequently leaves a mark on political communication. While social media tools are already adopted in political marketing, primarily in election campaigning, governments are still new in using social media. The aim of this study is to examine how Facebook is used by city mayors in countries of Central and Southeastern Europe in two months period, from March 1st to April 30th of 2012. Using content analysis we first analyzed status massages in order to see what kind of status messages they post: personal or political. Secondly, we conducted an analysis of comments on the examined statuses, in order to examine if citizens make constructive, cynical, supportive or neutral comments. We examined ten city mayors’ Facebook pages in five countries, Bulgaria, Croatia, Hungary, Macedonia and Slovenia. The results have revealed that city mayors in Central and Southeastern Europe use Facebook almost exclusively for official purposes. Secondly, the analysis of citizens’ comments demonstrates that expressing cynicism on Facebook is not the trend in these countries. The findings further confirm that Facebook is a good platform for gathering supporters, while there were no strong evidence found that it serves as platform for constructive discussion. The paper finally discusses how politician’s status messages can engage a larger number of citizens.Sve veći broj korisnika društvenih mreža ostavio je trag i na političku komunikaciju. Dok je upotreba društvenih mreža u političkom marketingu već uvriježena, prvenstveno u izbornim kampanjama, vlade i lokalna uprava i samouprava još su uvijek na početcima korištenja društvenih mreža. Cilj je ovog istraživanja ispitati kako gradonačelnici u zemljama srednje i jugoistočne Europe koriste Facebook. Koristeći analizu sadržaja, ispitali smo kakve status-poruke gradonačelnici stavljaju na svoje službene Facebook-stranice – privatne ili službene. Osim toga, analizirali smo komentare građana kako bismo utvrdili ostavljaju li građani konstruktivne, cinične, neutralne ili komentare potpore na stranicama gradonačelnika. Ispitano je deset službenih Facebook-stranica gradonačelnika u pet zemalja: Bugarskoj, Hrvatskoj, Mađarskoj, Makedoniji i Sloveniji. Rezultati istraživanja pokazali su da gradonačelnici u navedenim zemljama koriste Facebook gotovo isključivo u službene svrhe. Analiza komentara građana ukazuje kako trend iskazivanja cinizma na Facebooku nije prisutan u zemljama srednje i jugoistočne Europe. Nalazi dalje upućuju na činjenicu da je Facebook dobra platforma za okupljanje simpatizera, ali nisu pronađeni dokazi da Facebook služi kao platforma za konstruktivnu raspravu

Engaging stakeholders through Facebook. The case of Global Compact LEAD participants

Facebook has deeply modified the way people communicate and interact. From a business perspective, Facebook has enormous potential as a means of communication and stakeholder engagement. It enables companies to share contents rapidly and efficiently with a large number of stakeholders worldwide. People can personalise their Facebook profile to receive updates from selected companies. Moreover, people can reply to such posts or simply manifest their approval by liking or sharing the posts. In this way, people also propagate corporate information among their own friends. The dramatic diffusion of Facebook should encourage companies to virtually interact with a network of stakeholders 2.0, using Facebook as a stakeholder engagement tool. The evolution to Web 2.0 goes with a general change in the social and business environment. In today’s world, both policy makers and the public expect that companies work in a sustainable way and consult their stakeholders about corporate strategies, operations and performance. The discussion should concern social and ecological cares as well as economic issues. In this sense, the engagement of the Facebook community could considerable enlarge and improve the dialogue. This paper offers a theoretical and empirical analysis to answer the following research question: do sustainability-oriented companies use Facebook as an effective means of stakeholder engagement? The paper contains an investigation based on UN Global Compact LEAD members, characterised by strong commitment and cooperation with governments, civil society, labour and the UN in order to promote sustainable practices. To evaluate the contribution of Facebook to the dialogue on sustainability, the investigation considered the types of contents published by the LEAD companies on their Facebook pages in 30 days. According to the subject, seven categories of posts emerged from the analysis: human rights and social citizenship; labour; environment; anti-corruption; strategy, business activity and economic performance; news on products and services; other. To evaluate the use of Facebook for stakeholder engagement 2.0, the investigation verified how many “likes”, comments and “shares” each post received and how often the company replied. The analysis showed that some LEAD members did not have a Facebook profile, which is unacceptable nowadays. Moreover, the companies with an official page rarely covered all three perspectives of sustainability (social, environmental, and economic issues). Furthermore, companies rarely replied to stakeholders’ comments. Based on the empirical evidence, most LEAD participants should modify the way they used Facebook. Therefore, the results of this research may help them improve stakeholder engagement 2.0

Contested social representations of a religious ritual in the Philippines: Text mining online discourses on the Traslación

The article examines the production of contested social representations of a Philippine religious ritual in online spaces using a mixed methods approach to semantic network analysis. Comments from the online media coverage of the 2019 Traslación were mined from the Facebook pages of the eight most popular Philippine media outlets. A semantic network consisting of collocation of frequently used words was generated using R and Gephi. Network analysis produced three word clusters highlighting bifurcations linguistically, in the use of Filipino or English, and substantively, in contested representations. Analysis of these themes reveals the centrality of discourses reifying the ritual as authentic expressions of faith. A minority of discourses reflect criticisms of the Traslación as idolatry. This reflects the dichotomy of discourses in the Traslación literature. The research demonstrates the relevance of social computing in the analysis of meanings of cultural phenomena across large populations

It's Not All About Autism: the Emerging Landscape of Anti-Vaccination Sentiment on Facebook

Introduction: The anti-vaccination movement has been present since the early 1700s. Previous research suggests that social media may be fueling the spread of anti-vaccination messaging. Therefore, the purpose of this thesis is to (1) highlight major events in the history of the anti-vaccine movement, (2) present a stand-alone journal article from a systematic analysis of individuals known to express anti-vaccination sentiment on Facebook, and (3) integrate the conclusions presented in the article into a broader historical framework. Methods: A literature review was conducted for the historical overview. For the journal article, our data set consisted of 197 individuals with Facebook accounts who posted anti-vaccination comments on a prominent local pediatric clinic’s Facebook page. For each individual, we systematically analyzed publicly available content using quantitative coding, descriptive analysis, social network analysis, and an in-depth qualitative assessment. Results: Throughout history, the anti-vaccination movement has consistently sued fiery rhetoric and vivid imagery to spread its messages, which often center on concerns of liberty and safety. Analysis of Facebook profiles found that more individuals posted content related to mistrust in the medical community, liberty, and belief in homeopathic remedies compared to those who posted that vaccines cause autism. Among 136 individuals who divulged their location, 36 states and 8 countries outside the U.S. were represented. In a 2-mode network of individuals and topics, modularity analysis revealed 4 distinct sub-groups: (1) liberty, (2) naturalness, (3) illness, and (4) conspiracy. Qualitative analysis found that individuals often share posts from Facebook groups that market themselves as pro-science. Conclusion: Individuals on Facebook frequently posted anti-vaccine content that echoed historical concerns. Our findings suggest social media outlets facilitate anti-vaccination connection and organization, thus assisting in the amplification and diffusion of centuries’ old arguments and techniques. These findings are significant for public health in that they will inform the development of updated messaging around vaccination, and suggest the importance of understanding the history of the anti-vaccination movement when developing these messages. These findings also suggest a valuable opportunity for public health practitioners to leverage social networks to deliver more effective, tailored interventions to different constituencies

Detection of Americans’ Behavior toward Islam on Facebook

Social network websites have become a rich place for detecting and analyzing people’s attitudes, perceptions, and feelings towards news, products,  and other real-world issues. Facebook is a popular platform among different age groups and countries and is generally used to convey ideas about certain topics based on likes, comments and sharing. In recent years, one of the most controversial topics were the idea behind Islamophobia and other ideas built in people’s minds about Islam around the world. This research studied the public opinion of American citizens about Islam during the presidency of Donald Trump, as that period was rich in diversity of opinion between his supporters and detractors. In this paper, sentiment analysis was used to analyze American citizens’ behavior towards posts about Islam during Trump’s presidency in various states across the United States. Sentiment analysis was performed on Facebook posts and comments extracted from American news channels from the year 2017. Several machine learning methods were used to detect the polarity in the dataset. The highest classification accuracy among the classifiers used in this research was achieved using a logistic regression classifier, reaching 84%

Dukungan Sosial Melalui Media Sosial (Analisis Isi Kualitatif Pesan Dukungan Sosial Pada Halaman Facebook Rumah Zakat Official)

The developme nt of technology creates social networking sites that can connect many people through community groups online, the online community itself is a group of people who have the same goals mediated by computer media. In relation to the facebook page, this study aims to examine the form of social support on the facebook page Rumah Zakat Official . The type of research used in this research is qualitative by using qualitative content analysis approach. Sampling using non - probability sampling method while the technique used is purposive sampling by taking samples of posts and comments on the faceboo k page Rumah Zakat Official for one week there are 75 (seventy five) post messages (update status) with like as much 967,416 (Nine hundred sixty seven thousand four hundred and sixteen), distributed (sh are) of 7004 (seven thousand four ) and 1,445 comments (one thousand four hundred forty five) calculated manually. Technique of data retrieval is done by using documentation study in the form of screenshoot. While the data analysis techniques use data coding by using a deductive approach. The results of the re search on the facebook page of Rmuah Zakat Official are five forms of social support, such as: information support, emotional support, award support, instrumental support, and social network support. Of the five categories are the two most frequently excha nged categories of information support and emotional support. Keywords : Social Support, Rumah Zakat, Facebook, Facebook Page, Content Analysis, Qualitative