Influence Prediction on Social Media Network through Contents and Interaction Behaviors using Attention-based Knowledge Graph

2021 ◽  
Author(s):  
Quan M. Tran ◽  
Hien D. Nguyen ◽  
Binh T. Nguyen ◽  
Vuong T. Pham ◽  
Trong T. Le
Keyword(s):  
Social Media ◽  
Knowledge Graph ◽  
Interaction Behaviors ◽  
Social Media Network

Hacking in to the social media network of bacteria: The antiquorum sensing properties of herbs and spices

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381 ◽  
Author(s):  
S Cosa ◽  
AM Viljoen ◽  
SK Chaudhary ◽  
W Chen
Keyword(s):  
Social Media ◽  
Sensing Properties ◽  
The Social ◽  
Social Media Network ◽  
Herbs And Spices

scholarly journals Explaining Donation Behavior in Medical Crowdfunding in Social Media

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110145
Author(s):  
Zhengwei Huang ◽  
Jing Ouyang ◽  
Xiaohong Huang ◽  
Yanni Yang ◽  
Ling Lin
Keyword(s):  
Social Media ◽  
Interpersonal Relationship ◽  
Elaboration Likelihood ◽  
Perceived Trust ◽  
Likelihood Model ◽  
Social Media Platforms ◽  
Perceived Behavior Control ◽  
Donation Behavior ◽  
Depth Interviews ◽  
Social Media Network

Medical crowdfunding in social media is growing to be a convenient, accessible, and secure manner to cover medical expenses. It differs from traditional donation initiatives and medical crowdfunding on non-social media platforms in that projects are disseminated via social media network and among acquaintances. Through semi-structured in-depth interviews on donation behaviors of 52 respondents, this study uses grounded theory to extract seven main categories that affect medical crowdfunding donation behavior in social media, namely interpersonal relationship, reciprocity of helping, attitude toward donation, perceived behavior control, perceived trust, project information, and characteristics of patients. In the spirit of Elaboration Likelihood Model, we develop a theoretical framework that the seven factors influence donation behavior in medical crowdfunding in social media via a central and a peripheral route.

Impact of Social Media Usage on Information Retrieval Among Undergraduate Students in Faculty of Management Sciences, University of Ilorin

2020 ◽  
pp. 406-436
Author(s):  
Evelyn Olakitan Akinboro ◽  
Taylor Morenikeji Olayinka
Keyword(s):  
Social Media ◽  
Information Retrieval ◽  
Undergraduate Students ◽  
Sources Of Information ◽  
Media Usage ◽  
Social Media Networks ◽  
Gender And Age ◽  
Use Of Social Media ◽  
Types Of Information ◽  
Social Media Network

The chapter examined the impact of social media on information retrieval among undergraduate students in Faculty of Management Science, University of Ilorin. It determined the social media network that undergraduate students are more exposed to for retrieving information, identifying the differences in undergraduate students' usage of social media network for information retrieval based on gender and age brackets, exploring preference for social media compared to other sources of information retrieval system available for students, exploring the types of information retrieved from social media network, and identifying the challenges faced by undergraduates in the use of social media networks. The population of the study was comprised of 3,634 students out of which a sample of 360 was chosen through stratified random technique. A self-designed questionnaire was used to collect data. Five research questions were developed and answered by the study. The findings revealed that undergraduate students' exposure to social media is very high.

scholarly journals Earthquake Shake Detecting by Data Mining from Social Network Platforms

2020 ◽  
Vol 10 (3) ◽  
pp. 812
Author(s):  
Yu-Jung Chuo
Keyword(s):  
Social Media ◽  
Semantic Analysis ◽  
Bulletin Board ◽  
Tree Model ◽  
Detection Model ◽  
The Social ◽  
Network Platform ◽  
Scale Detection ◽  
Central Weather Bureau ◽  
Social Media Network

This study used social media posts of the related effect of earthquakes to derive seismic shake scale distributions in regions of Taiwan and compared it with the regional seismic scale reported by the Central Weather Bureau (CWB) of Taiwan. This study conducted a context searching to scrawl the relationship phrase on the social media network platform, PTT bulletin board system (BBS), to detect the earthquake shake scale using the keywords of the context. In this investigation a decision tree model for analyzing the semantic words from the context of the target event to detect the earthquake shake scale was devised. The results indicate that we can pick out the keywords to use to detect the earthquake shake scale at about 85%. Furthermore, the results of the derived shake scale show that the four studied cases are in a good agreement with the presented news from the CWB of Taiwan. In this study, the author attempted to develop a quick earthquake shake scale detection model by semantic analysis of the collected earthquake disaster information reported on the social media network platform.

To share is to receive: News as social currency for social media reciprocity

2020 ◽  
Vol 9 (1) ◽  
pp. 3-20
Author(s):  
Edson C. Tandoc ◽  
Alice Huang ◽  
Andrew Duffy ◽  
Rich Ling ◽  
Nuri Kim
Keyword(s):  
Social Media ◽  
Panel Survey ◽  
Self Presentation ◽  
Social Currency ◽  
One Year ◽  
To Receive ◽  
News Sharing ◽  
Social Media Network

Guided by the framework of reciprocity on social media, the current study investigated antecedents of news sharing. Using a two-wave panel survey involving 868 respondents who took two surveys about one year apart, this study examined the effect of frequency of receiving news on social media on subsequent news-sharing behaviour, while controlling for demographics, news-sharing motivations and trust in social media news. The study found that motivation for self-presentation and trust in news shared by one's social media network positively predicted news sharing on social media. Frequency of receiving news at Time 1 also predicted sharing news subsequently at Time 2. This points to news being valued as a form of social currency.

scholarly journals A Survey of Data Mining Techniques on Information Networks

2018 ◽  
Vol 7 (2.6) ◽  
pp. 293
Author(s):  
Sadhana Kodali ◽  
Madhavi Dabbiru ◽  
B Thirumala Rao
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Information Networks ◽  
Information Network ◽  
Heterogeneous Information ◽  
Data Mining Techniques ◽  
Heterogeneous Information Networks ◽  
Web Objects ◽  
The Social ◽  
Social Media Network

An Information Network is the network formed by the interconnectivity of the objects formed due to the interaction between them. In our day-to-day life we can find these information networks like the social media network, the network formed by the interaction of web objects etc. This paper presents a survey of various Data Mining techniques that can be applicable to information networks. The Data Mining techniques of both homogeneous and heterogeneous information networks are discussed in detail and a comparative study on each problem category is showcased.

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