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In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.
This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: • Sentic Computing's multi-disciplinary appro...
Sentiment analysis research has been started long back and recently it is one of the demanding research topics. Research activities on Sentiment Analysis in natural language texts and other media are gaining ground with full swing. But, till date, no concise set of factors has been yet defined that really affects how writers’ sentiment i.e., broadly human sentiment is expressed, perceived, recognized, processed, and interpreted in natural languages. The existing reported solutions or the available systems are still far from perfect or fail to meet the satisfaction level of the end users. The reasons may be that there are dozens of conceptual rules that govern sentiment and even there are possibly unlimited clues that can convey these concepts from realization to practical implementation. Therefore, the main aim of this book is to provide a feasible research platform to our ambitious researchers towards developing the practical solutions that will be indeed beneficial for our society, business and future researches as well.
Microblogs and social media platforms are now considered among the most popular forms of online communication. Through a platform like Twitter, much information reflecting people’s opinions and attitudes is published and shared among users on a daily basis. This has recently brought great opportunities to companies interested in tracking and monitoring the reputation of their brands and businesses, and to policy makers and politicians to support their assessment of public opinions about their policies or political issues. A wide range of approaches to sentiment analysis on social media, have been recently built. Most of these approaches rely mainly on the presence of affect words or syntac...
A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.
The Handbook consists of four major sections. Each section is introduced by a main article: Theories of Emotion – General Aspects Perspectives in Communication Theory, Semiotics, and Linguistics Perspectives on Language and Emotion in Cultural Studies Interdisciplinary and Applied Perspectives The first section presents interdisciplinary emotion theories relevant for the field of language and communication research, including the history of emotion research. The second section focuses on the full range of emotion-related aspects in linguistics, semiotics, and communication theories. The next section focuses on cultural studies and language and emotion; emotions in arts and literature, as w...
The two-volume set LNAI 8265 and LNAI 8266 constitutes the proceedings of the 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, held in Mexico City, Mexico, in November 2013. The total of 85 papers presented in these proceedings were carefully reviewed and selected from 284 submissions. The first volume deals with advances in artificial intelligence and its applications and is structured in the following five sections: logic and reasoning; knowledge-based systems and multi-agent systems; natural language processing; machine translation; and bioinformatics and medical applications. The second volume deals with advances in soft computing and its applications and is structured in the following eight sections: evolutionary and nature-inspired metaheuristic algorithms; neural networks and hybrid intelligent systems; fuzzy systems; machine learning and pattern recognition; data mining; computer vision and image processing; robotics, planning and scheduling and emotion detection, sentiment analysis and opinion mining.
This two-volume set of IFIP AICT 617 and 618 constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference "Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation" on Transfer and Diffusion of IT, TDIT 2020, held in Tiruchirappalli, India, in December 2020. The 86 revised full papers and 36 short papers presented were carefully reviewed and selected from 224 submissions. The papers focus on the re-imagination of diffusion and adoption of emerging technologies. They are organized in the following parts: Part I: artificial intelligence and autonomous systems; big data and analytics; blockchain; diffusion and adoption technology; emerging technologies in e-Governance; emerging technologies in consumer decision making and choice; fin-tech applications; healthcare information technology; and Internet of Things Part II: information technology and disaster management; adoption of mobile and platform-based applications; smart cities and digital government; social media; and diffusion of information technology and systems
Machines are being systematically empowered to be interactive and intelligent in their operations, offerings. and outputs. There are pioneering Artificial Intelligence (AI) technologies and tools. Machine and Deep Learning (ML/DL) algorithms, along with their enabling frameworks, libraries, and specialized accelerators, find particularly useful applications in computer and machine vision, human machine interfaces (HMIs), and intelligent machines. Machines that can see and perceive can bring forth deeper and decisive acceleration, automation, and augmentation capabilities to businesses as well as people in their everyday assignments. Machine vision is becoming a reality because of advancement...