Transparency in Social Media

Abstract

A series of authored and edited monographs that utilize quantitative and computational methods to model, analyze and interpret large-scale social phenomena. Titles within the series contain methods and practices that test and develop theories of complex social processes through bottom-up modeling of social interactions. Of particular interest is the study of the co-evolution of modern communication technology and social behavior and norms, in connection with emerging issues such as trust, risk, security and privacy in novel socio-technical environments.Computational Social Sciences is explicitly transdisciplinary: quantitative methods from fields such as dynamical systems, artificial intelligence, network theory, agentbased modeling, and statistical mechanics are invoked and combined with state-ofthe-art mining and analysis of large data sets to help us understand social agents, their interactions on and offline, and the effect of these interactions at the macro level. Topics include, but are not limited to social networks and media, dynamics of opinions, cultures and conflicts, socio-technical co-evolution and social psychology. Computational Social Sciences will also publish monographs and selected edited contributions from specialized conferences and workshops specifically aimed at communicating new findings to a large transdisciplinary audience. A fundamental goal of the series is to provide a single forum within which commonalities and differences in the workings of this field may be discerned, hence leading to deeper insight and understanding. Series EditorsMore information about this series at

Dampak Covid-19: Guru Mengadopsi Media Sosial Sebagai E-Learning Pada Pembelajaran Jarak Jauh

“…Karena media social mampu diterapkan sebagai e-learning dan memberikan hasil belajar yang tinggi, mampu menguatkan motivasi dan Pengguna media sosial (Alhabash & Ma, 2017& Al-ali, 2014, media social diadpsi dalam pembelajaran (Ugorji I Ogbonnaya, 2019) menunjukkan bahwa Pengguna media social memiliki keutamaan dalam kejelasan dan dapat diterapkan dalam pembelajaran jarak jauh sebagai e-learning. Skala "Efisiensi (Efficiency)" memiliki 4 item dengan hasil nilai berada pada tolak ukur Sangat baik (Excellent), waktu dan tempat yang tidak ditetapkan dan tidak ditentukan membuat Pengguna media social menjadi efisien, dapat belajar dimana dan dalam aktivitas apa pun, media social dapat digunakan untuk efisien presentasi pembelajaran (Lauren Reichart , memiliki kekuatan tranparansi sebagai media social dalam pembelajaran dan aktivitas manusia modern dengan teknologi (Sorin Adam Matei, 2015) dan interkasi secara public dengan baik menggunakan media social (Marta Dynel, 2015).…”