Lurkers, creepers, and virtuous interactivity: From property rights to consent and care as a conceptual basis for privacy concerns and information ethics

First Monday ◽  
2016 ◽  
Author(s):  
Dylan Eric Wittkower
Keyword(s):  
Data Mining ◽  
Social Networking ◽  
Social Networking Sites ◽  
Personal Information ◽  
Conceptual Basis ◽  
Feminist Ethics ◽  
Privacy Concerns ◽  
Data Ownership ◽  
Phenomenological Perspective ◽  
Informational Economy

Exchange of personal information online is usually conceptualized according to an economic model that treats personal information as data owned by the persons these data are ‘about.’ This leads to a distinct set of concerns having to do with data ownership, data mining, profits, and exploitation, which do not closely correspond to the concerns about privacy that people actually have. A post-phenomenological perspective, oriented by feminist ethics of care, urges us to figure out how privacy concerns arrive in fundamentally human contexts and to speak to that, rather than trying to convince people to care about privacy as it is juridically conceived and articulated. By considering exchanges of personal information in a human-to-human online informational economy — being friends on social networking sites — we can identify an alternate set of concerns: consent, respect, lurking, and creepiness. I argue that these concerns will provide a better guide to both users and companies about prudence and ethics in information economies than the existing discourse around ‘privacy.’

scholarly journals Measuring individuals’ concerns over collective privacy on social networking sites

2016 ◽  
Vol 10 (1) ◽  
Author(s):  
Haiyan Jia ◽  
Heng Xu
Keyword(s):  
Social Networking ◽  
Private Information ◽  
Social Networking Sites ◽  
Structural Model ◽  
Personal Information ◽  
Information Access ◽  
Three Dimensions ◽  
Online Information ◽  
Privacy Concerns ◽  
Starting Point

With the rise of social networking sites (SNSs), individuals not only disclose personal information but also share private information concerning others online. While shared information is co-constructed by self and others, personal and collective privacy boundaries become blurred. Thus there is an increasing concern over information privacy beyond the individual perspective. However, limited research has empirically examined if individuals are concerned about privacy loss not only of their own but their social ties’; nor is there an established instrument for measuring the collective aspect of individuals’ privacy concerns. In order to address this gap in existing literature, we propose a conceptual framework of individuals’ collective privacy concerns in the context of SNSs. Drawing on the Communication Privacy Management (CPM) theory (Petronio, 2002), we suggest three dimensions of collective privacy concerns, namely, collective information access, control and diffusion. This is followed by the development and empirical validation of a preliminary scale of SNS collective privacy concerns (SNSCPC). Structural model analyses confirm the three-dimensional conceptualization of SNSCPC and reveal antecedents of SNS users’ concerns over violations of the collective privacy boundaries. This paper serves as a starting point for theorizing privacy as a collective notion and for understanding online information disclosure as a result of social interaction and group influence.

scholarly journals Data Mining Technics and Cyber Hygiene Behaviors in Social Media

2021 ◽  
Vol 2 (2) ◽  
pp. 2503-2515
Author(s):  
Hanna Martyniuk ◽  
Valeriy Kozlovskiy ◽  
Serhii Lazarenko ◽  
Yuriy Balanyuk
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Personal Information ◽  
Data Sets ◽  
Personal Privacy ◽  
Data Mining Techniques ◽  
Social Network Data

The authors present in this work information about social media and data mining usage for that. It is represented information about social networking sites, where Facebook dominates the industry by boasting an account of 85% of the internet user’s worldwide. Applying data mining techniques to large social media data sets has the potential to continue to improve search results for everyday search engines, realize specialized target marketing for businesses, help psychologist study behavior, provide new insights into social structure for sociologists, personalize web services for consumers, and even help detect and prevent spam for all of us. The most common data mining applications related to social networking sites is represented. Authors have also gave information about different data mining techniques and list of these techniques. It is important to protect personal privacy when working with social network data. Recent publications highlight the need to protect privacy as it has been shown that even anonymizing this type of data can still reveal personal information when advanced data analysis techniques are used. A whole range of different threat of social networks is represented. Authors explain cyber hygiene behaviors in social networks, such as backing up data, identity theft and online behavior.

scholarly journals Visualization for Analysis of Social Networking, Models and Techniques: A Review

2018 ◽  
Vol 6 (4) ◽  
pp. 137-144
Author(s):  
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Privacy Concerns ◽  
Clustering Techniques ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Network Analyser ◽  
Twitter Users

In this paper, we have reviewed several social networking sites, evolution and background and significance of social media. Social networking is used as platform for various applications like: government, business, educational, political, dating and matrimonial, etc. Motivation is to examine adversarial networks and represents the activities observed by analyser. Additionally we’ve examined social network model and operations performed in it along with simulation and close degree algorithm, Adversarial Network analyser and analysis of vulnerabilities of an organization analysed. We examine the types of posting on social media websites and influence of posting data and privacy concerns of Facebook and twitter users. This study indicates the different concerns of users regarding posting information and its influences of user based privacy concerns. In addition we discussed several classification and clustering techniques used for data mining in online social networking sites and the market targets and parameters and analysis of different variables as per the usage of SNSs.

Social Networking Sites Continuance: An Application of Extended Theory of Planned Behaviour

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Himanshu Rajput
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Theory Of Planned Behaviour ◽  
Standard Theory ◽  
Planned Behaviour ◽  
Privacy Concerns ◽  
Proposed Model ◽  
Continued Use ◽  
Moderating Role

Social networking sites (SNSs) have become popular in India with the proliferation of Internet. SNSs have gained the interests of academicians and researchers. The current study is an endeavor to understand the continuance of social networking sites in India. The study applies an extended version of theory of planned behavior. Additional factors privacy concerns and habits were incorporated into the standard theory of planned behaviour. A survey was conducted in a Central University in India. Overall, data was collected from 150 respondents. PLS-SEM was used to test the proposed model. All the hypotheses except the moderating role of habits between intentions and continued use of social networking sites, were supported by the results. Habits were found to affect continued use of social networking sites indirectly through continued intentions.

Need for Dynamicity in Social Networking Sites

2014 ◽  
pp. 64-87
Author(s):  
Gurdeep S Hura
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Big Data ◽  
Social Networking ◽  
Real World ◽  
Social Networking Sites ◽  
Data Science ◽  
Emerging Technology ◽  
New Applications ◽  
Future Status

This chapter presents this new emerging technology of social media and networking with a detailed discussion on: basic definitions and applications, how this technology evolved in the last few years, the need for dynamicity under data mining environment. It also provides a comprehensive design and analysis of popular social networking media and sites available for the users. A brief discussion on the data mining methodologies for implementing the variety of new applications dealing with huge/big data in data science is presented. Further, an attempt is being made in this chapter to present a new emerging perspective of data mining methodologies with its dynamicity for social networking media and sites as a new trend and needed framework for dealing with huge amount of data for its collection, analysis and interpretation for a number of real world applications. A discussion will also be provided for the current and future status of data mining of social media and networking applications.

Impact of Social Networking Sites Among College Students With Special Reference to Rural Areas in India

2020 ◽  
pp. 124-147
Author(s):  
T. Balamurugan ◽  
M. Aravinthan
Keyword(s):  
Standard Deviation ◽  
University Students ◽  
Social Networking ◽  
Rural Areas ◽  
Social Networking Sites ◽  
Social Engagement ◽  
Personal Information ◽  
Normal Activity ◽  
Student Community ◽  
The University

Social networking sites over the years have changed from a few user-based sites into a phenomena that has become a platform for a huge number of users. However, the growth and development of social networking sites have brought great concerns on parents and educational authorities with respect to potential risks that are facing the university students as they use online social networking frequently for gathering information. The use of social networking sites among the university students requires much attention with increasing number of students creating profile and feeding their personal information into the sites. The increasing activity on the sites by student community can negatively impact the normal activity of students' lives. This can also become a hindrance to the academic development as well as social engagement of students. Therefore, there is a need to study, assess, and evaluate the issues revolving the usage of social networking sites among the student community. The study shows that the distribution of respondents according to their influence of SNS. It shows both section-wise distribution and their composite scores. Also, the table shows the respective mean scores and standard deviation. It may be inferred that 77.50% of the respondents have stated that the influence of SNS are high, 18.55% of the respondents have stated that the influence of SNS is moderate, and 3.95% of the respondents have stated that the influence of SNS is low. However, the composite mean score (2.72), standard deviation (0.530) depicts that the respondents have stated that the influence of SNS is high.

“Hey, Look at My Body!”

2014 ◽  
Vol 4 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Lik Sam Chan ◽  
Hing Weng Eric Tsang
Keyword(s):  
Social Media ◽  
Body Image ◽  
Young Adults ◽  
Hong Kong ◽  
Social Networking ◽  
Social Networking Sites ◽  
Body Image Satisfaction ◽  
Privacy Concerns ◽  
Privacy Risks ◽  
The Relationship

This article considers the phenomenon of online body display by users of social networking sites in Hong Kong. A survey of 392 young adults was conducted to investigate the relationships between narcissism, grandiose exhibitionism, body image satisfaction, perceived privacy risks, and online body display. A Body Display Index was developed to measure the perceived level of sexual explicitness of photographs shared by Facebook users. Grandiose exhibitionism, a sub-trait of narcissism, was found to be a stronger predictor of online body display than narcissism. The relationship between body image satisfaction and online body display was not significant, and no relationship was found between such displays and perceived privacy risks, thus implying a lack of social media-related privacy concerns among the respondents.

scholarly journals Self-disclosure in social networking sites

2015 ◽  
Vol 25 (2) ◽  
pp. 279-299 ◽  
Author(s):  
Christy Cheung ◽  
Zach W. Y. Lee ◽  
Tommy K. H. Chan
Keyword(s):  
Social Influence ◽  
Social Networking ◽  
Social Exchange ◽  
Social Networking Sites ◽  
Service Providers ◽  
Personal Information ◽  
Integrated Model ◽  
Perceived Benefits ◽  
Self Disclosure ◽  
Content Type

Purpose – The purpose of this paper is to examine the relative impacts of perceived cost, perceived benefits, and social influence on self-disclosure behaviors in social networking sites under an integrated theoretical framework. Design/methodology/approach – Building upon social exchange theory and privacy calculus theory, an integrated model was developed. The model was tested empirically using a sample of 405 social networking site’s users. Users were required to complete a survey regarding self-disclosure behaviors in Facebook. Findings – The results indicate that social influence is the factor which exhibits the strongest effect on self-disclosure in social networking sites, followed by perceived benefits. Surprisingly, perceived privacy risk does not have any significant impact on self-disclosure. Research limitations/implications – The results inform researchers about the importance to incorporate social influence factors and cultural factors into future online self-disclosure study. Practical implications – The results suggest that users focus on the benefits as well as social influence when they decide to reveal personal information in social networking sites, but pay less attention to the potential privacy risks. Educators are advised to launch educational programs to raise students’ awareness to the potential risks of self-disclosure in social networking sites. Service providers of social networking sites are encouraged to provide intuitive privacy indices showing users the levels of privacy protection. Originality/value – This paper is one of the first to develop and empirically tests an integrated model of self-disclosure in social networking sites.

Self-Disclosure on Social Networking Sites

2015 ◽  
Vol 43 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Kaan Varnali ◽  
Aysegul Toker
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Personal Information ◽  
Subjective Norm ◽  
Self Disclosure ◽  
Self Monitoring ◽  
Willingness To Disclose ◽  
Independent Effects ◽  
The Impact ◽  
Public Self Consciousness

Our aim was to contribute to the understanding of self-disclosure behavior on social networking sites (SNS). Participants (N = 1,294) completed online surveys comprising measures of willingness to disclose personal information on SNS, self-esteem, SNS affinity, self-disclosure, honesty of self-disclosure, subjective norm, self-monitoring skills, and public self-consciousness. Our findings suggest that self-disclosure mediates the impact of communication-based personality characteristics on the use of SNS, and that subjective norm and SNS affinity also have significant independent effects.

Medical students’ and residents’ use of online social networking tools: Implications for teaching professionalism in medical education

First Monday ◽  
2008 ◽  
Author(s):  
Richard E Ferdig ◽  
Kara Dawson ◽  
Erik W Black ◽  
Nicole M. Paradise Black ◽  
Lindsay A. Thompson
Keyword(s):  
Medical Education ◽  
Medical Students ◽  
Social Networking ◽  
Social Networking Sites ◽  
Personal Information ◽  
Southeastern United States ◽  
Professional Lives ◽  
Online Tools ◽  
Types Of Information ◽  
Social Networking Tools

This study sought to determine if and how 501 medical students and 312 residents are using Facebook at a large university in the Southeastern United States. Results reveal that medical students and residents are using Facebook and about two-thirds of users maintain public profiles. While there is variation in the types of information provide within profiles, many medical students seem unaware of or unconcerned with the possible ramifications of sharing personal information in publicly-available online profiles even though such information could impact their professional lives. Thus, this study provides data based evidence that online tools such as social networking sites should become a part of the dialogue related to preparing future physicians to meet the Accreditation Council on Graduate Medical Education (ACGE) professionalism competency.

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