Predicting Future Alleviation of Mental Illness in Social Media: An Empathy-Based Social Network Perspective

Emotive Trending And Tracking of Tweets

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i11.463 ◽

2017 ◽

Vol 7 (11) ◽

pp. 25

Author(s):

Sanjay Chhataru Gupta

Keyword(s):

Social Networks ◽

Social Media ◽

Social Network ◽

The Social ◽

The World ◽

Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

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ANALISIS PERINGKAT TOP BRAND OJEK ONLINE MENGGUNAKAN JEJARING SOSIAL PERCAKAPAN TWITTER

Jurnal Ilmiah Informatika Komputer ◽

10.35760/ik.2019.v24i2.2365 ◽

2019 ◽

Vol 24 (2) ◽

pp. 88-104

Author(s):

Ilham Aminudin ◽

Dyah Anggraini

Keyword(s):

Social Media ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Path Length ◽

Average Path Length ◽

Average Degree ◽

Clustering Coefficient ◽

R Programming

Banyak bisnis mulai muncul dengan melibatkan pengembangan teknologi internet. Salah satunya adalah bisnis di aplikasi berbasis penyedia layanan di bidang moda transportasi berbasis online yang ternyata dapat memberikan solusi dan menjawab berbagai kekhawatiran publik tentang layanan transportasi umum. Kemacetan lalu lintas di kota-kota besar dan ketegangan publik dengan keamanan transportasi umum diselesaikan dengan adanya aplikasi transportasi online seperti Grab dan Gojek yang memberikan kemudahan dan kenyamanan bagi penggunanya Penelitian ini dilakukan untuk menganalisa keaktifan percakapan brand jasa transportasi online di jejaring sosial Twitter berdasarkan properti jaringan. Penelitian dilakukan dengan dengan mengambil data dari percakapan pengguna di social media Twitter dengan cara crawling menggunakan Bahasa pemrograman R programming dan software R Studio dan pembuatan model jaringan dengan software Gephy. Setelah itu data dianalisis menggunakan metode social network analysis yang terdiri berdasarkan properti jaringan yaitu size, density, modularity, diameter, average degree, average path length, dan clustering coefficient dan nantinya hasil analisis akan dibandingkan dari setiap properti jaringan kedua brand jasa transportasi Online dan ditentukan strategi dalam meningkatkan dan mempertahankan keaktifan serta tingkat kehadiran brand jasa transportasi online, Grab dan Gojek.

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New Democracy in Digital Era through Social Media and News Online

Humaniora ◽

10.21512/humaniora.v11i1.6182 ◽

2020 ◽

Vol 11 (1) ◽

pp. 13

Author(s):

Abitassha Az Zahra ◽

Eko Priyo Purnomo ◽

Aulia Nur Kasiwi

Keyword(s):

Social Media ◽

Social Network ◽

Communication Networks ◽

Social Communication ◽

Development Policy ◽

Online News ◽

Digital Era ◽

The Social ◽

New Democracy

The research aimed to explain the pattern of social communication on the issue of rejection of the PLTU Batang development policy. It used data on Twitter accounts involved in the rejection of the PLTU Batang development policy. In analyzing existing data, qualitative methods and social analysis networks were used. To see social networks in the rejection of the PLTU Batang development policy, the research used the NodeXL application to find out the patterns of social communication networks in #TolakPLTUBatang. From the results, it can be seen that in the dissemination of social networking information, the @praditya_wibby account is the most central account in the social network and has a strong influence on the social network. The @praditya_wibby account has a role in moving the community through Twitter to make a critical social movement. This means that in the current digital era, democracy enters a new form through the movement of public opinion delivery through social media. Besides, by encouraging the role of online news, the distribution of information becomes faster to form new perceptions of an issue. This is evident from the correlation network where the @praditya_wibby account has correlations with several compass online media accounts, tirto.id, okezonenews, vice, antaranews, BBCIndonesia, and CNN Indonesia.

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Measuring Relevant Information in Health Social Network Conversations and Clinical Diagnosis Cases (Preprint)

10.2196/preprints.11475 ◽

2018 ◽

Author(s):

Albert Moreira ◽

Raul Alonso-Calvo ◽

Alberto Muñoz ◽

Jose Crespo

Keyword(s):

Social Media ◽

Social Network ◽

Relevant Information ◽

Online Discussions ◽

Biomedical Knowledge ◽

Expert Opinions ◽

Health Related ◽

Health Social Network ◽

Discussion System ◽

Clinical Cases

BACKGROUND Internet and Social media is an enormous source of information. Health Social Networks and online collaborative environments enable users to create shared content that afterwards can be discussed. While social media discussions for health related matters constitute a potential source of knowledge, characterizing the relevance of participations from different users is a challenging task. OBJECTIVE The aim of this paper is to present a methodology designed for quantifying relevant information provided by different participants in clinical online discussions. METHODS A set of key indicators for different aspects of clinical conversations and specific clinical contributions within a discussion have been defined. These indicators make use of biomedical knowledge extraction based on standard terminologies and ontologies. These indicators allow measuring the relevance of information of each participant of the clinical conversation. RESULTS Proposed indicators have been applied to two discussions extracted from PatientsLikeMe, as well as to two real clinical cases from the Sanar collaborative discussion system. Results obtained from indicators in the tested cases have been compared with clinical expert opinions to check indicators validity. CONCLUSIONS The methodology has been successfully used for describing participant interactions in real clinical cases belonging to a collaborative clinical case discussion tool and from a conversation from a Health Social Network.

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