Social computing privacy and online relationships

Social computing has revolutionized interpersonal communication. It has introduced the aspect of social relationships which people can utilize to communicate with the vast spectrum of their contacts. However, the major Online Social Networks (OSNs) have been found to be falling short of appropriately accommodating these relationships in their privacy controls which leads to undesirable consequences for the users. This paper highlights some of the shortcomings of the OSNs with respect to their handling of social relationships and enumerates numerous challenges which need to be conquered in order to provide users with a truly social experienc

Recommending access control decisions to social media users

Social media has become an integral part of the Internet and has revolutionized interpersonal communication. The lines of separation between content creators and content consumers have blurred as normal users have platforms such as social media sites, blogs and microblogs at their disposal on which they can create and consume content as well as have the opportunity to interact with other users. This change has also led to several well documented privacy problems for the users. The privacy problems faced by social media users can be categorized into institutional privacy (related to the social network provider) and social privacy (related to the interpersonal communication between social media users) problems. The work presented in this thesis focuses on the social privacy issues that affect users on social media due to their interactions with members in their network who may represent various facets of their lives (such as work, family, school, etc.). In such a scenario, it is imperative for them to be able to appropriately control access to their information such that it reaches the appropriate audience. For example, a person may not want to share the same piece of information with their boss at work and their family members. These boundaries are defined by the nature of relationships people share with each other and are enforced by controlling access during communication. In real life, people are accustomed to do this but it becomes a greater challenge while interacting online. The primary contribution of the work presented in this thesis is to design an access control recommendation mechanism for social media users which would ease the burden on the user while sharing information with their contacts on the social network. The recommendation mechanism presented in this thesis, REACT (REcommending Access Control decisions To social media users), leverages information defining interpersonal relationships between social media users in conjunction with information about the content in order to appropriately represent the context of information disclosure. Prior research has pointed towards ways in which to employ information residing in the social network to represent social relationships between individuals. REACT relies on extensive empirical evaluation of such information in order to identify the most suitable types of information which can be used to predict access control decisions made by social media users. In particular, the work in this thesis advances the state of art in the following ways: (i) An empirical study to identify the most appropriate network based community detection algorithm to represent the type of interpersonal relationships in the resulting access control recommendation mechanism. This empirical study examines a goodness of fit of the communities produced by 8 popular network based community detection algorithms with the access control decisions made by social media users. (ii) Systematic feature engineering to derive the most appropriate profile attribute to represent the strength or closeness between social media users. The relationship strength is an essential indicator of access control preferences and the endeavor is to identify the minimal subset of attributes which can accurately represent this in the resulting access control recommendation mechanism. (iii) The suitable representation of interpersonal relationships in conjunction with information about the content that result in the design of an access control recommendation mechanism, REACT, which considers the overall context of information disclosure and is shown to produce highly accurate recommendations

Effect of nano-additives on epoxy composites

Nanoparticle incorporation is a convenient way to enhance the mechanical properties of polymer matrices. In the last number of years abundant research has been done published concerning the enhancement of the mechanical properties of nanoparticle filled polymers. This work analyses the influence of nano clay and nano carbon reinforcement on the behavior of epoxy matrices. The nanoparticles were dispersed into the epoxy resin using a direct mixing method. Specimen preparation and testing were carried out as per ASTM standards. The investigation reveals that, due to incorporation of nano additives in epoxy composite to some extent give encouraging results when compared with the neat epoxy. After a certain amount of addition of additives these properties do not get enhanced and in some cases on further addition of additives the properties get depleted/deteriorated

How socially aware are social media privacy controls?

Social media sites are key mediators of online communication. Yet the privacy controls for these sites are not fully socially aware, even when privacy management is known to be fundamental to successful social relationships

IMPROVE:Identifying Minimal PROfile VEctors for similarity based access control

There is ample evidence which shows that social media users struggle to make appropriate access control decisions while disclosing their information and smarter mechanisms are needed to assist them. Using profile information to ascertain similarity between users and provide suggestions to them during the process of making access control decisions has been put forth as a possible solution to this problem. This paper presents an empirical study aimed at identifying the minimal subset of attributes which are most suitable for being used to create profile vectors for the purpose of predicting access control decisions. We begin with an exhaustive list of 30 profile attributes and identify a subset of 2 profile attributes which are shown to be sufficient in obtaining similarity between profiles and predicting access control decisions with the same accuracy as previous models. We demonstrate that using this pair of attributes will help mitigate the challenges encountered by similarity based access control mechanisms

Non-sharing communities?:an empirical study of community detection for access control decisions

Social media users often find it difficult to make appropriate access control decisions which govern how they share their information with a potentially large audience on these platforms. Community detection algorithms have been previously put forth as a solution which can help users by automatically partitioning their friend network. These partitions can then be used by the user as a basis for making access control decisions. Previous works which leverage communities for enhancing access control mechanisms assume that members of the same community will have the same access to a user’s content, but whether or to what extent this assumption is correct is a lingering question. In this paper, we empirically evaluate a goodness of fit between the communities created by implementing 8 community detection algorithms on the friend networks of users and the access control decisions made by them during a user study. We also analyze whether personal characteristics of the users or the nature of the content play a role in the performance of the algorithms. The results indicate that community detection algorithms may be useful for creating default access control policies for users who exhibit a relatively more static access control behaviour. For users showing great variation in their access control decisions across the board (both in terms of number and actual members), we found that community detection algorithms performed poorly

Digitalization, Convergence and The Film Industry

This research examines the strategic direction of firms in the film industry which are posed with challenges of growth and sustainability in a dynamically changing environment which is an outcome of rapid industry convergence fuelled by technological advancements which span the last decade. With an ongoing initiative within the industry which is aimed at digital migration, influx of internet, communications and other related industries which could possibly alter the course of strategy formulation at organizational level. This research attempts at studying a set of diverse literature on strategy and further relating it to firms in practice. This research utilises qualitative means of gathering data which are both; primary and secondary in nature. The collated data is further subject to analysis using the Porters’ Five Forces in order to understand the current and the anticipated climate while an industry level analysis stresses on the nature of firm’s growth patterns and resource set allocations within the industry. The secondary data set is analysed to gain an insight into the digital migration timeframe which aides the research in drawing out future course of strategic formulation. The Five Forces framework reveals a shift in bargaining power of firms at different levels while the industry level analysis indicates growth patterns in current and future integration efforts both; horizontal and vertical. The third set of analysis focuses on value chain disintermediation which is informed by Porters’ Five Forces and Industry level analysis. The threat to auxiliary businesses is highlighted by this analysis. Different strategic choices with firms are discussed with relevance to the findings, current industry composition, growth patterns and finally the new digital paradigm which the industry awaits