Angebote zu "Sentiment" (60 Treffer)

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Twitter : Sentiment Analysis of Current Affairs
54,90 € *
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Sentiment Analysis is an important type of text analysis that aims to support decision making by extracting & analyzing opinion text. Identifying positive & negative opinions & measuring how positively & negatively an entity is regarded. Sentiment analysis of social media data while the use of machine learning classifier for predicting the sentiment orientation provides a useful tool for the users to monitor brand or product sentiment.As more & more user express their views & opinion on twitter. So twitter becomes valuable sources of people's opinions. Tweets data can be used to infer people's opinion about marketing & social studies that can spot general people's opinion in regard to the social event which is going to be in current on twitter. Using this can obtain greater accuracy and identify people's opinion.

Anbieter: Dodax
Stand: 29.01.2020
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Sentiment Analysis On The Topic Of Fitness Usin...
35,90 € *
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This research focuses on the public's sentiment towards the topic of fitness, with the Online Social Network (OSN) Twitter used as the source of data collected and analysed. Having a strong passion for fitness myself, I wanted to see how in the growing access to gyms and the marketing of the "perfect body", how ones sentiment changes over a period of time whilst attempting to achieve such goals. From the analysis of over 23 million tweets collected between late December 2013 and early February 2014 a number of trends are identified and discussed within this book.

Anbieter: Dodax
Stand: 29.01.2020
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Sentiment Analysis On The Topic Of Fitness Usin...
37,00 € *
ggf. zzgl. Versand

This research focuses on the public's sentiment towards the topic of fitness, with the Online Social Network (OSN) Twitter used as the source of data collected and analysed. Having a strong passion for fitness myself, I wanted to see how in the growing access to gyms and the marketing of the "perfect body", how ones sentiment changes over a period of time whilst attempting to achieve such goals. From the analysis of over 23 million tweets collected between late December 2013 and early February 2014 a number of trends are identified and discussed within this book.

Anbieter: Dodax AT
Stand: 29.01.2020
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Data Mining for Tweet Sentiment Classification
49,00 € *
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The goal of this work is to classify short Twitter messages with respect to their sentiment using data mining techniques. Twitter messages, or tweets, are limited to 140 characters. This limitation makes it more difficult for people to express their sentiment and as a consequence, the classification of the sentiment will be more difficult as well. The sentiment can refer to two different types: emotions and opinions. This research is solely focused on the sentiment of opinions. These opinions can be divided into three classes: positive, neutral and negative. The tweets are then classified with an algorithm to one of those three classes. Known supervised learning algorithms as support vector machines and naive Bayes are used to create a prediction model. Before the prediction model can be created, the data has to be pre-processed from text to a fixed-length feature vector. The features consist of sentiment-words and frequently occurring words that are predictive for the sentiment. The learned model is then applied to a test set to validate the model.

Anbieter: Dodax
Stand: 29.01.2020
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Data Mining for Tweet Sentiment Classification
50,40 € *
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The goal of this work is to classify short Twitter messages with respect to their sentiment using data mining techniques. Twitter messages, or tweets, are limited to 140 characters. This limitation makes it more difficult for people to express their sentiment and as a consequence, the classification of the sentiment will be more difficult as well. The sentiment can refer to two different types: emotions and opinions. This research is solely focused on the sentiment of opinions. These opinions can be divided into three classes: positive, neutral and negative. The tweets are then classified with an algorithm to one of those three classes. Known supervised learning algorithms as support vector machines and naive Bayes are used to create a prediction model. Before the prediction model can be created, the data has to be pre-processed from text to a fixed-length feature vector. The features consist of sentiment-words and frequently occurring words that are predictive for the sentiment. The learned model is then applied to a test set to validate the model.

Anbieter: Dodax AT
Stand: 29.01.2020
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Intelligent System for Visualized Data Analytics
37,00 € *
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The chapter 1 discusses about the importance of the social media in the day to day life and how users are utilizing their services. It summarizes why web users opted social media for data analysis and for daily decision making process. This chapter discussed about the definitions of the sentiment analysis and opinion mining. This chapter explains how sentiments or opinions are expressed, by web users. The chapter 2 discusses about the literature study of this research domain on the popular social networking sites, taking some example sites like twitter, amazon, flipkart etc., and various tools available for the task of sentiment analysis. This chapter discusses about, what is intelligent system. We have shown different sentiment classification levels and sentiment analysis methodology. The chapter 3 discusses about the system design for this research domain. This chapter depicts a model diagram of an intelligent system that processing the twitter data, and the complete diagram of the intelligent system for visualized data analytics and the data flow diagram of the sentiment analysis variation of social data.

Anbieter: Dodax AT
Stand: 29.01.2020
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Intelligent System for Visualized Data Analytics
35,90 € *
ggf. zzgl. Versand

The chapter 1 discusses about the importance of the social media in the day to day life and how users are utilizing their services. It summarizes why web users opted social media for data analysis and for daily decision making process. This chapter discussed about the definitions of the sentiment analysis and opinion mining. This chapter explains how sentiments or opinions are expressed, by web users. The chapter 2 discusses about the literature study of this research domain on the popular social networking sites, taking some example sites like twitter, amazon, flipkart etc., and various tools available for the task of sentiment analysis. This chapter discusses about, what is intelligent system. We have shown different sentiment classification levels and sentiment analysis methodology. The chapter 3 discusses about the system design for this research domain. This chapter depicts a model diagram of an intelligent system that processing the twitter data, and the complete diagram of the intelligent system for visualized data analytics and the data flow diagram of the sentiment analysis variation of social data.

Anbieter: Dodax
Stand: 29.01.2020
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Visual and Text Sentiment Analysis through Hier...
50,89 € *
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This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis.The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book's novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments, stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit, evaluation of HGFRNNs with different types of recurrent units, and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.

Anbieter: Dodax AT
Stand: 29.01.2020
Zum Angebot
Visual and Text Sentiment Analysis through Hier...
50,89 € *
ggf. zzgl. Versand

This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis.The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book's novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments, stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit, evaluation of HGFRNNs with different types of recurrent units, and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.

Anbieter: Dodax
Stand: 29.01.2020
Zum Angebot