Sentiment analysis social networks (16 resultados)

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Taschenbuch. Condición: Neu. Sentiment Analysis in Social Networks | Federico Albert Pozzi | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2016 | Elsevier Inc | EAN 9780128044124 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Paperback. Condición: Brand New. 136 pages. 8.66x5.91x0.31 inches. In Stock.

Taschenbuch. Condición: Neu. Gauging affectivity in social networks | A Sentiment Analysis module for evaluating continuous student opinions | Lum Zhaveli | Taschenbuch | 136 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659465406 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Condición: New. Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining S.

Taschenbuch. Condición: 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.…

Taschenbuch. Condición: 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.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Sentiment analysis is a new field of research that is getting very popular due to the demand to understand what are people's thoughts or opinions in the internet. There are major challenges to understand natural language and how to classify opinions with high accuracy. To classify student opinions a system has been created that approaches the problem in two ways, using fixed-rules and using machine learning algorithms. The classifier that are created are able to classify student opinions as positive and negative. The dataset that created contains more than 250 student opinions that were gathered and processed. Evaluation of various algorithms that were used to classify opinions is performed in order to learn what will suit best the case with the current data-set. The system uses excessively dictionaries with positive and negative words when fixed-rules approach is used, and the data-set's are used for other machine learning algorithms. Input is processed in lexical and syntactical level before it is used to train the model and to be classified. The system that we chose to receive student opinions and to use the classifiers is Effectinet, developed by a student at CITY College.…