Effects of social media usage and social media multitasking on the academic performance of university students

Sarcastic sentiment detection in tweets streamed in real time: a big data approach

Enhancing the role of flow experience in social media usage and its impact on shopping

With the rapid development of information communication technology, social media has become a necessary part of people’s daily life. Recently, many music teachers have applied social media to augme...

Exploring the aids of social media for musical instrument education

Social media, in recent times, has with eased an explosion of data with so many social media platforms available to interact and express opinions freely. This has led to easy access to the privacy of social media users which raise broader security concerns and issues. The present paper provides an overview of various sentiment analysis approaches and techniques for social media security and analytics. The multiple security application domains like deception detection, anomaly detection, risk management, and disaster relief have been identified where sentiment analysis is used for social media security. An in‐depth study on security issues related to data provenance, distrust, e‐commerce security, consumer security breaches, market surveillance, credibility, and risk assessment in social media have been presented. A comparison of various techniques, methodologies, dataset, and application domain where sentiment analysis is used has been discussed. The present work discusses the results of different machine learning techniques based on the performance metrics that have been used for the implementation of sentiment analysis in the respective security domains. It identifies the various gaps, issues, and the recent advancements in the field and presents a line of work that needs to be carried forward in future.

Role of sentiment analysis in social media security and analytics

Overview of current state-of-the-art of social media for NTI Working Group III: Societal Verification

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State-of-the-Art of Social Media Analytics Research

In response to the growing pervasiveness of mobile technologies such as tablets and smartphones, the International Atomic Energy Agency and the U.S. Department of Energy National Laboratories have been exploring the potential use of these platforms for international safeguards activities. Specifically of interest are information systems (software, and accompanying servers and architecture) deployed on mobile devices to increase the situational awareness and productivity of an IAEA safeguards inspector in the field, while simultaneously reducing paperwork and pack weight of safeguards equipment. Exploratory development in this area has been met with skepticism regarding the ability to overcome technology deployment challenges for IAEA safeguards equipment. This report documents research conducted to identify potential challenges for the deployment of a mobile collaborative information system to the IAEA, and proposes strategies to mitigate those challenges.

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Zoe N. Gastelum

Papers

State-of-the-Art of Social Media Analytics Research

Feasibility Study of Implementing a Mobile Collaborative Information Platform for International Safeguards Inspections

The Cognitive Effects of Machine Learning Aid in Domain-Specific and Domain-General Tasks