Are ICT/web 2.0 tools influencing civic engagement in modern democracies? An exploratory analysis from India

Web 2.0 tools, while mobilising citizens to make informed choices, may also manipulated public opinion. This hypothesis forms the central theme of this research investigation through the historiography lens. Based on concurrent research from decade, the authors take a closer look at citizen-to-citizen engagement, so as to trace the role of web 2.0 tools, in perhaps manipulating public opinion or enabling democratic governance through reversal of some existing defects in the Indian context. Specifically, they raise these questions: Has ICT enabled civic engagement manipulated public opinion in this developing democracy? Has it succeeded in reversing apparent defects in the electoral system, which is regarded pivotal in democracies? Focusing on the elections, the authors present a synopsis of the use of web 2.0 tools which were seemingly efficiently and prolifically used during the elections albeit to reach out to the large population base in this country.

Exploring the effectiveness of true abnormal data elimination in context-aware web services recommendation

Recent years have witnessed a growing interest in context-aware recommender system (CARS), which explores the impact of context factors on personalized Web services recommendation. Basically, the general idea of CARS methods is to mine historical service invocation records through the process of context-aware similarity computation. It is observed that traditional similarity mining process would very likely generate relatively big deviations of QoS values, due to the dynamic change of contexts. As a consequence, including a considerable amount of deviated QoS values in the similarity calculation would probably result in a poor accuracy for predicting unknown QoS values. In allusion to this problem, this paper first distinguishes two definitions of Abnormal Data and True Abnormal Data, the latter of which should be eliminated. Second, we propose a novel CASR-TADE method by incorporating the effectiveness of True Abnormal Data Elimination into context-aware Web services recommendation. Finally, the experimental evaluations on a real-world Web services dataset show that the proposed CASR-TADE method significantly outperforms other existing approaches.