Analyzing Controversial Topics within Facebook

Social media plays a significant role in the dissemination of information. Now more than ever, consumers turn to social media sites (SMS) to catch up on current events and share their perspectives. While this form of communication is enjoyed by the public, it also has its drawbacks. Because many perspectives can be captured via SMS, this often leads to public discourse and in some cases, controversy. Misinformation and disinformation continue to spread throughout the internet allowing many consumers to become misinformed. This further elevates such discourse and allows for real issues to be forgotten as online debate spirals out of reality and false information gains traction. Given the issues at hand, this paper seeks to demonstrate a rudimentary measurement of curve fitting as a proof of concept for capturing controversy on Facebook using the reactions of its user base toward controversial topics

Hubungan Perilaku Cyberbullying di Media Sosial dengan Tingkat Kecemasan pada Mahasiswa S1 Keperawatan UMKT

Tujuan Studi : Tujuan dari penelitian ini untuk menganalisis Hubungan Perilaku Cyberbullying di Media Sosial dengan Tingkat Kecemasan Pada Mahasiswa S1 Keperawatan Universitas Muhammadiyah Kalimantan Timur. Metodologi : Penelitian ini menggunakan pendekatan kuantitatif desain Cross Sectional dengan jumlah responden 107 mahasiswa.Analisis yang digunakan dalam penelitian ini adalah analisis bivariat dengan menggunakan uji statistik yaitu uji Chi Square / Fisher Exact dengan derajat kepercayaan 95% (α = 0,05). Hasil : Hasil penelitian menunjukkan adanya hubungan antara perilaku cyberbullying di media sosial dengan tingkat kecemasanpada mahasiswa S1 Keperawatan Universiitas Muhammadiyah Kalimantan Timur dengan nilai p-value = 0.001< 0.05. Manfaat : Hasil penelitian ini dapat dijadikan sebagai bahan evaluasi dalam penyelenggaraan program pendidikan ilmu kesehatan masyarakat, sebagai indikator keberhasilan dalam proses belajar mengajar selama perkuliahan, sebagai sumber referensi dan acuan dalam penelitian berikutnya serta sebagai informasi mengenai hubungan perilaku cyberbullying di media sosial dengan tingkat kecemasan pada mahasiswa keperawatan UMK

Characterizing Controversiality of Topics Utilizing Eccentricity of Opinions

Access to abundant biased information in echo chambers and social bubbles often intensifies opinions to the extremes. The extremization of opinions results in several topics becoming controversial. However, it is very difficult to measure the degree of controversiality of a topic objectively since the controversiality of any topic is subjective and perceived differently from different communities. The absence of an objective measure of controversiality has been a major hindrance in understanding the causes and effects of it. In this work we propose a method to quantify controversiality of a topic by utilizing eccentricity of opinions on that topic. The eccentricity of an opinion is the amount of strangeness of the opinion relative to other opinions in the social neighborhood. The collective eccentricity of all opinions for a topic works as an indicator of the controversiality of that topic and can be represented by any measure of central tendency. With the help of social network data, we also demonstrate that opinions on several issues related to our routine life show similar trends for diversity though they differ in their controversiality

Progressive view on social justice: Netizen opinions about social justice warrior

Social justice warrior (SJW) is a pejorative term for individuals who fight for equality, environment, and gender. Because their progressive morals radically differ from the predominant values, the so-called social justice warriors spark controversies. This study aimed to describe netizens’ opinions about SJW and describe the dynamics of conflict or support in more detail. Text mining and opinion coding were used to elicit research data. The opinions that we gathered were analyzed in 2 stages: sentiment analysis and content analysis. The results of sentiment analysis are negative (445), neutral (86), and positive (90). Content analysis of the negative opinions showed the characteristics of sarcastic, rude, critical, and contemptuous (mocking/disrespecting). The style of positive sentiments (comments congruent with the phenomena) is divided into supportive, empathic, and motivational opinions. Negative opinions are more dominant because of netizens’ self-acceptance, the effects of informal social control in cyberspace, SJW’s presumed social non-compliance, and doubts of objectivity. Positive opinions can be explained by criticism of social contract theory, namely the demand to be more supportive of minority groups, sensitivity, and empathy (the ability to feel other groups' social conditions and environmental conditions).