Content Analysis of Privacy Management Features in Geosocial Networking Application

Abstract

Geosocial networking application allows user to share information and communicate with other people within a virtual neighborhood or community. Although most geosocial networking application include privacy management features, one the challenge is to improve privacy management features design. To overcome this challenge, the adaptation of privacy-related theories offers a concrete way to comprehend and analyze how the privacy management features are used as tangible research results that facilitate user and system developer in understanding privacy management. This paper attempt to propose a standardized privacy management features in geosocial networking application from market perspectives that could be utilized by researchers and application developers to demonstrate or measure privacy management features. The objective of this paper is two-fold: First, to map the theoretical constructs guided by Communication Privacy Management (CPM) theory into privacy management features in geosocial networking application. Second, to evaluate the reliability of the proposed features using content analysis. Content analysis is performed on 1326 geosocial networking apps in the market (Google Play store and App Store) to determine the reliability of the proposed privacy management features through inter-coder reliability analysis. The primary findings of the content analysis show that many of the privacy management features with low reliability are from Boundary Turbulence construct. Furthermore, only 6 out of 13 proposed features are deemed reliable, namely, specific grouping, visibility setting, privacy policy, violation, imprecision and inaccuracy. The proposed privacy management features may aid researchers and system developers to focus on the best privacy management features for improving geosocial networking application design.

Authors and Affiliations

Syarulnaziah Anawar, Yeoh Wai Hong, Erman Hamid, Zakiah Ayop

Keywords

Related Articles

 E-Shape Micro strip Patch Antenna on Different Thickness for pervasive Wireless Communication

[i][/i] In this Paper Presents the result for different standard thickness values, and the result is performed by thickness of 31 mile, Ku- band frequency 12GHz are gives the best result. The antenna has become a ne...

Performance Evaluation of SIFT and Convolutional Neural Network for Image Retrieval

Convolutional Neural Network (NN) has gained a lot of attention of the researchers due to its high accuracy in classification and feature learning. In this paper, we evaluated the performance of CNN used as feature for i...

  Fingerprint Image Enhancement:Segmentation to Thinning

  Fingerprint has remained a very vital index for human recognition. In the field of security, series of Automatic Fingerprint Identification Systems (AFIS) have been developed. One of the indices for evaluating the...

Fault-Tolerant Model Predictive Control for a Z(TN)-Observable Linear Switching Systems

This work considers the control and the state observation of a linear switched systems with actuators faults. A particular problem is studied: the occurrence of non-observable subsystem in the switching sequence. Hence,...

Developing Cross-lingual Sentiment Analysis of Malay Twitter Data Using Lexicon-based Approach

Sentiment analysis is a process of detecting and classifying sentiments into positive, negative or neutral. Most sentiment analysis research focus on English lexicon vocabularies. However, Malay is still under-resourced....

Download PDF file
  • EP ID EP417722
  • DOI 10.14569/IJACSA.2018.091166
  • Views 106
  • Downloads 0

How To Cite

Syarulnaziah Anawar, Yeoh Wai Hong, Erman Hamid, Zakiah Ayop (2018). Content Analysis of Privacy Management Features in Geosocial Networking Application. International Journal of Advanced Computer Science & Applications, 9(11), 476-484. https://europub.co.uk/articles/-A-417722