Sentiment Analysis in Social Networks

Federico Alberto Pozzi, Elisabetta Fersini, Enza Messina, Bing Liu

Sentiment Analysis in Social Networks

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商品描述

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
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
Shows how to apply opinion mining 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

商品描述(中文翻譯)

情感分析的目標是定義能夠從自然語言文本中提取主觀信息（如意見和情感）的自動工具，以便創建結構化且可操作的知識，供決策支持系統或決策者使用。隨著社交網絡的出現和發展，情感分析的價值更加突出。

《社交網絡中的情感分析》首先概述了該領域的最新研究趨勢，然後討論了社交網絡互動背後的社會學和心理學過程。本書探討了解決在線社交網絡中具有上下文依賴性和動態文本的語義和機器學習模型和方法，展示了社交網絡流由於其大規模、短小、噪聲、上下文依賴性和動態性而帶來的眾多挑戰。

此外，本書還具有以下特點：
- 從多個計算領域（包括自然語言處理、機器學習、大數據和統計方法）採用跨學科方法
- 提供有關意見垃圾郵件、推理和社交網絡分析的見解
- 展示如何應用情感分析工具於特定應用和領域，以及如何獲得最佳結果以理解後果
- 作為社交媒體分析領域最新技術的一站式參考資料
- 從多個計算領域（包括自然語言處理、大數據和統計方法）採用跨學科方法
- 提供有關意見垃圾郵件、推理和社交網絡挖掘的見解
- 展示如何應用意見挖掘工具於特定應用和領域，以及如何獲得最佳結果以理解後果
- 作為社交媒體分析領域最新技術的一站式參考資料

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