The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologiesProvides insights into opinion spamming, reasoning, and social network analysisShows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequencesServes as a one-stop reference for the state-of-the-art in social media analytics
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Dr. Federico Alberto Pozzi received the Ph.D. in Computer Science at the University of Milano - Bicocca (Italy). His Ph.D. thesis is focused on Probabilistic Relational Models for Sentiment Analysis in Social Networks. His research interests primarily focus on Data Mining, Text Mining, Machine Learning, Natural Language Processing and Social Network Analysis, in particular applied to Sentiment Analysis and Community Discovery in Social Networks. He currently works at SAS Institute (Italy) as Senior Solutions Specialist - Integrated Marketing Management & Analytics.
Dr. Elisabetta Fersini is currently a postdoctoral research fellow at the University of Milano - Bicocca (Italy). Her research activity is mainly focused on statistical relational learning with particular interests in supervised and unsupervised classification. The research activity finds application to Web/Text mining, Sentiment Analysis, Social Network Analysis, e-Justice and Bioinformatics. She actively participated to several national and international research projects. She has been an evaluator for international research projects and member of different scientific committees. She co-founded an academic spin-off specialized in sentiment analysis and community discovery in social networks.
Prof. Enza Messina is a Professor in Operations Research at the Department of Informatics Systems and Communications, University of Milano-Bicocca, where she leads the research Laboratory MIND (Models in decision making and data analysis). She holds a Ph.D. in Computational Mathematics and Operations Research from the University of Milano. Her research activity is mainly focused on decision models under uncertainty and more recently on statistical relational models for data analysis and knowledge extraction. In particular, she developed relational classi_x000C_cation and clustering models that finds applications in different domains such as systems biology, e-justice, text mining and social network analysis.
Dr Bing Liu is an Associate Professor at the College of Agriculture, Nanjing Agricultural University, China. He received his PhD in Information Agriculture in 2016 from Nanjing Agricultural University. His research areas include extreme climate effects on crop growth, yield, and quality; agricultural systems modelling; and climate change impact assessment and adaptation.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: BGV Books LLC, Murray, KY, U.S.A.
Condizione: Good. Exact ISBN match. Immediate shipping. No funny business. Codice articolo 9780128044124
Quantità: 1 disponibili
Da: WorldofBooks, Goring-By-Sea, WS, Regno Unito
Paperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Codice articolo GOR011609139
Quantità: 1 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Englisch. Codice articolo 9780128044124
Quantità: 2 disponibili
Da: Chiron Media, Wallingford, Regno Unito
PF. Condizione: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Codice articolo 6666-IUK-9780128044124
Quantità: 20 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 26774128-n
Quantità: Più di 20 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 26774128
Quantità: Più di 20 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 26774128-n
Quantità: Più di 20 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In English. Codice articolo ria9780128044124_new
Quantità: Più di 20 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics. Codice articolo 9780128044124
Quantità: 2 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 26774128
Quantità: Più di 20 disponibili