scholarly journals Young Investors’ Instagram Usage Behavior and Investment Risk Appetite

2021 ◽  
Vol 1 (1) ◽  
pp. 15
Author(s):  
Gesti Memarista ◽  
Angela Merici Adinda Puspita
Keyword(s):  
Social Network ◽  
Social Networking Sites ◽  
Online Social Network ◽  
Risk Tolerance ◽  
Investment Risk ◽  
Social Connection ◽  
Online Questionnaire ◽  
Risk Appetite ◽  
Usage Behavior ◽  
Financial Consultant

Online Social Network Sites (SNSs) provides a lot of information to understanding young investor behavior. As the interest of financial practitioners, the young investor has their own risk tolerance. So, this study aims to predict the investment risk appetite through the social networking sites (SNSs) as one of huge informations exchange platforms by using young investors’ Instagram usage behavior. This research uses investment risk appetite and extroversion personality as the dependent variables. Moreover, number of followers on Instagram, time spent on Instagram, frequency of log on to Instagram, the use of Instagram for self-expression, and the use of Instagram for social connection as the independent variables. The researchers use 300 young stock investors through online questionnaire. The results study show that number of followers on Instagram and the use of Instagram for social connection significantly affect the extroversion personality, the extroversion personality significantly affect the investment risk appetite. Otherwise, time spent on Instagram, frequency of log on to Instagram, the use of Instagram for self-expression do not significantly affect the extroversion personality. This result obtains the probability of understanding the young investor’s risk appetite through their Instagram usage behavior, so the financial consultant can gather the information to understand their current social network activities.

scholarly journals Online social networks as formal learning environments: Learner experiences and activities

2012 ◽  
Vol 13 (1) ◽  
pp. 144 ◽  
Author(s):  
George Veletsianos ◽  
Cesar Navarrete
Keyword(s):  
Social Network ◽  
Social Networking ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Learning Experience ◽  
Online Social Network ◽  
Online Course ◽  
Formal Learning ◽  
The Social

<p>While the potential of social networking sites to contribute to educational endeavors is highlighted by researchers and practitioners alike, empirical evidence on the use of such sites for formal online learning is scant. To fill this gap in the literature, we present a case study of learners’ perspectives and experiences in an online course taught using the Elgg online social network. Findings from this study indicate that learners enjoyed and appreciated both the social learning experience afforded by the online social network and supported one another in their learning, enhancing their own and other students’ experiences. Conversely, results also indicate that students limited their participation to course-related and graded activities, exhibiting little use of social networking and sharing. Additionally, learners needed support in managing the expanded amount of information available to them and devised strategies and “workarounds” to manage their time and participation.<br /><strong></strong></p>

Building Online Social Networks to Engage Female Students in Information Systems

2015 ◽  
Vol 10 (4) ◽  
pp. 33-51
Author(s):  
Jaymeen R. Shah ◽  
Hsun-Ming Lee
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Information Systems ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Role Models ◽  
Online Social Network ◽  
Research Process ◽  
Female Students ◽  
The Social

During the next decade, enrollment growth in Information Systems (IS) related majors is unlikely to meet the predicted demand for qualified IS graduates. Gender imbalance in the IS related program makes the situation worse as enrollment and retention of women in the IS major has been proportionately low compared to male. In recent years, majority of high school and college students have integrated social networking sites in their daily life and habitually use these sites. Providing female students access to role models via an online social network may enhance their motivation to continue as an IS major and pursue a career in IS field. For this study, the authors follow the action research process – exploration of information systems development. In particular, a Facebook application was developed to build the social network connecting role models and students. Using the application, a basic framework is tested based on the gender of participants. The results suggest that it is necessary to have adequate number of role models accessible to students as female role-models tend to select fewer students to develop relationships with a preference for female students. Female students likely prefer composite role models from a variety of sources. This pilot study yields valuable lessons to provide informal learning fostered by role modeling via online social networks. The Facebook application may be further expanded to enhance female students' interests in IS related careers.

scholarly journals Security and Privacy of Online Social Network Applications

2013 ◽  
pp. 206-221
Author(s):  
Willem De Groef ◽  
Dominique Devriese ◽  
Tom Reynaert ◽  
Frank Piessens
Keyword(s):  
Social Network ◽  
Social Networking Sites ◽  
Online Social Network ◽  
Third Party ◽  
Security And Privacy ◽  
Security Risks ◽  
Privacy And Security ◽  
Network Applications ◽  
Recent Innovation ◽  
Social Applications

An important recent innovation on social networking sites is the support for plugging in third-party social applications. Together with the ever-growing number of social network users, social applications come with privacy and security risks for those users. While basic mechanisms for isolating applications are well understood, these mechanisms fall short for social-enabled applications. It is an interesting challenge to design and develop application platforms for social networks that enable the necessary functionality of social applications without compromising both users’ security and privacy. This chapter will identify and discuss the current security and privacy problems related to social applications and their platforms. Next, it will zoom in on proposals on how to address those problems.

scholarly journals SCIENTIFIC WAY TO IDENTIFY DUPLICATE PROFILE IN SOCIAL NETWORKING WEBSITES

2016 ◽  
Vol 2 (2) ◽  
Author(s):  
PANKAJ PANKAJ
Keyword(s):  
Social Network ◽  
Social Networking ◽  
Social Networking Sites ◽  
Online Social Network ◽  
Security Attacks ◽  
The Real ◽  
Individual User ◽  
Active User ◽  
On Line ◽  
Privacy Violation

In present scenario an Individual user will have multiple social network accounts to stay involved with friends in several social networking sites. Online social network users aren’t attentive to the varied security attacks like privacy violation, fraud, etc. Different on-line social users can assume it as real users and that they could be capable them that aren’t truly the real user.It is estimated 1.96 billion user are active on social networking sites. Only Facebook have 1.87 billion active user in a month.. During this research paper, I had tried to analyze social network knowledge supported attributes similarity. The planned system will cite as several similar social network profiles as a potential and analyze them so as to seek out whether or not it belongs to same or totally different persons. It makes different user straightforward to speak with one another during a safe and secure manner.

scholarly journals A Privacy-Enhanced Friending Approach for Users on Multiple Online Social Networks

Computers ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 42 ◽  
Author(s):  
Erfan Aghasian ◽  
Saurabh Garg ◽  
James Montgomery
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Online Social Network ◽  
Privacy Preserving ◽  
User Participation ◽  
Computationally Efficient ◽  
Efficient Manner ◽  
Sensitivity Score

Online social network users share their information in different social sites to establish connections with individuals with whom they want to be a friend. While users share all their information to connect to other individuals, they need to hide the information that can bring about privacy risks for them. As user participation in social networking sites rises, the possibility of sharing information with unknown users increases, and the probability of privacy breaches for the user mounts. This work addresses the challenges of sharing information in a safe manner with unknown individuals. Currently, there are a number of available methods for preserving privacy in order to friending (the act of adding someone as a friend), but they only consider a single source of data and are more focused on users’ security rather than privacy. Consequently, a privacy-preserving friending mechanism should be considered for information shared in multiple online social network sites. In this paper, we propose a new privacy-preserving friending method that helps users decide what to share with other individuals with the reduced risk of being exploited or re-identified. In this regard, the first step is to calculate the sensitivity score for individuals using Bernstein’s polynomial theorem to understand what sort of information can influence a user’s privacy. Next, a new model is applied to anonymise the data of users who participate in multiple social networks. Anonymisation helps to understand to what extent a piece of information can be shared, which allows information sharing with reduced risks in privacy. Evaluation indicates that measuring the sensitivity of information besides anonymisation provides a more accurate outcome for the purpose of friending, in a computationally efficient manner.

The Effect of Engagement in Online Social Network on Susceptibility to Influence

2015 ◽  
Vol 42 (2) ◽  
pp. 201-223 ◽  
Author(s):  
S P. Tussyadiah ◽  
Devi Roza Kausar ◽  
Primidya K. M. Soesilo
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Networking ◽  
Peer Influence ◽  
Social Networking Sites ◽  
Positive Relationship ◽  
Online Social Network ◽  
Consumer Participation ◽  
Social Prestige ◽  
Tourism And Hospitality

The effect of consumer participation in online social networking activities on their susceptibility to influence is investigated in a context of restaurant consumption. This research identified a positive relationship between consumers engagement in social networking sites (SNS) on their susceptibility to global consumption influence, which is a multidimensional factor consisting of conformity to trend, social prestige, and quality perception. Furthermore, consumer engagement in SNS and susceptibility to global consumption influence positively affect social influence on SNS. That is, consumers with higher participation in SNS are more prone to global consumer convergence and peer influence on SNS. As implications for tourism and hospitality businesses, strategies to manage consumer-to-consumer communication on social media are suggested.

scholarly journals A Machine Learning-based Online Social Network Analysis for 360-degree User Profiling

2019 ◽  
Vol 9 (2S2) ◽  
pp. 992-998
Keyword(s):  
Machine Learning ◽  
Social Network ◽  
Social Networking Sites ◽  
Online Social Network ◽  
User Profiling ◽  
Machine Learning Technique ◽  
The People ◽  
Learning Technique ◽  
The Government ◽  
Personal Interests

This paper aims to analyse the online social network for reconnaissance of people for finding their potentiality. The work considers one of the famous social networking sites, Twitter, where people express their thoughts and ideas, through which the people in the site knowingly or unknowingly reveal the information about themselves such as personal interests, likes and dislikes. The Machine Learning technique facilitates the work to mine the tweet data of a person to get his/her 360-degree profiling. This profiling is helpful to identify the personality type of a person, which is essential for the Government to identify the people involved in spreading the fake news in Twitter.

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