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Social Media Mining
Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.
MELODY OF LIFE
MELODY OF LIFE, is a collection of poetries and short stories by different co-authors from all over India. Each writer has penned down their views in such a way that you’ll feel empowered, happy and also experience the impact of words. These writers have used the power of their words silently to express their imagination. The main reason behind the publication of this book is to create love and awareness towards literature in our new generation and to provide a platform for all the emerging writers to show case their talent.
History of Islam (Vol 2)
In this second volume, starting with the Caliphate of Banu Umayyah, the martyrdom of Imam Husain (R) and the Caliphate of the Abbasids, all areas have been covered as far as the expansion of Islam was. --Publisher description.
Tuḥfah Yi- ʻAbbāsī
This book is one of the oldest and most important sources written on the esoteric teachings of Islam from a Shi'ite perspective. It demonstrates the Qur'anic origins of Sufism and its close relationship with Shi'ism. The book is based mainly on the teachings of the Qur'an, Hadith narrations of Shi'ite Imams, and the teachings of earlier Sufi masters. In this lies the uniqueness, authenticity, and strength of the book. Tuhfah yi-' Abbasi is written in a typical prose style of the Safavid period and is replete with Arabic words and phrases. The difficulty and dryness of the style, however, is properly compensated by timely quotation of Prophetic traditions, narrations of the Shi'ite Imams, and Sufi poetry composed by 'Attar, Rumi, Hafiz, Mansur Hallaj, as well as the author. This work conveys a universal message for all human beings, particularly at a time when Sufism and Shi'ism are misrepresented by pseudo-Sufis and extremist Shi'ite, and misunderstood by many readers in the Muslim world and in the West.
Computational Trust Models and Machine Learning
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book: Explains how reputation-based systems are used to determine trust in diverse online communities Describes how machine learning techniques are employed to build robust reputation systems Explores two distinctive approaches to determining credibility of resources—one where the human role is implicit, and one that leverages human input explicitly Shows how decision support can be facilitated by computational trust models Discusses collaborative filtering-based trust aware recommendation systems Defines a framework for translating a trust modeling problem into a learning problem Investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions Computational Trust Models and Machine Learning effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.
Detecting Fake News on Social Media
In the past decade, social media has become increasingly popular for news consumption due to its easy access, fast dissemination, and low cost. However, social media also enables the wide propagation of "fake news," i.e., news with intentionally false information. Fake news on social media can have significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area that is attracting tremendous attention. This book, from a data mining perspective, introduces the basic concepts and characteristics of fake news across disciplines, reviews representative fake news detection methods in a principled way, and illustrates challenging i...
Social Computing, Behavioral-Cultural Modeling and Prediction
This book constitutes the refereed proceedings of the 7th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2014, held in Washington, DC, USA, in April 2014. The 51 full papers presented were carefully reviewed and selected from 101 submissions. The SBP conference provides a forum for researchers and practitioners from academia, industry, and government agencies to exchange ideas on current challenges in social computing, behavioral-cultural modeling and prediction, and on state-of-the-art methods and best practices being adopted to tackle these challenges. The topical areas addressed by the papers are social and behavioral sciences, health sciences, military science, and information science.
