社交大数据挖掘

Anisha P. Rodrigues, N. Chiplunkar, Roshan Fernandes
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引用次数: 0

摘要

社交媒体被用来在一大群人之间分享数据或信息。许多论坛、博客、社交网络、新闻报道、电子商务网站和更多的在线媒体在分享个人观点方面发挥着作用。从这些来源生成的数据是巨大的,并且是非结构化的格式。大数据是一个术语,用于庞大或复杂的数据集,传统的处理系统无法处理。情感分析是应用于大数据的主要数据分析方法之一。判断文本是否包含主观信息以及它所表达的信息是自然语言处理的一项任务。它有助于实现各种目标,如测量客户满意度、观察公众对政治运动的情绪、电影销售预测、市场情报等等。在本章中,作者介绍了用于情感分析的各种技术以及使用这些技术的相关工作。本章还提出了情感分析领域的开放问题和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social Big Data Mining
Social media is used to share the data or information among the large group of people. Numerous forums, blogs, social networks, news reports, e-commerce websites, and many more online media play a role in sharing individual opinions. The data generated from these sources is huge and in unstructured format. Big data is a term used for data sets that are large or complex and that cannot be processed by traditional processing system. Sentimental analysis is one of the major data analytics applied on big data. It is a task of natural language processing to determine whether a text contains subjective information and what information it expresses. It helps in achieving various goals like the measurement of customer satisfaction, observing public mood on political movement, movie sales prediction, market intelligence, and many more. In this chapter, the authors present various techniques used for sentimental analysis and related work using these techniques. The chapter also presents open issues and challenges in sentimental analysis landscape.
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