基于大数据挖掘的网络媒体舆情分析模型及实施方案

Xinge Zhang
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引用次数: 0

摘要

随着互联网应用的快速增长,网络平台上积累了大量的公众意见数据,为利用大数据技术进行公众意见分析带来了巨大的机遇。与云计算等新的网络应用类似,基于计算机和网络的进步,物联网(IoT)、移动互联网和大数据技术吸引了人们的研究兴趣。然而,关于大数据驱动的网络媒体公众评论的研究还处于起步阶段,相关的分析模型及其实施方案还有待进一步明确。在此背景下,提出本研究旨在厘清基于大数据的网络媒体公众评论信息维度模型及其作用机制,进而表达基于大数据的网络媒体公众评论分析模型的实施方案。该模型包括信息收集技术、文本聚类技术和信息预处理技术。本工作的研究成果有助于在大数据时代从海量数据中高效挖掘和识别公众评论信息,对网络媒体的公众评论监督和指导具有借鉴意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Public Comment Analysis Model of Network Media Based on Big Data Mining and Implementation Plans
With the rapid increase of Internet application, a large volume of public comment data is accrued on the network platform and brings a great opportunity to the public comment analysis using big data technology. Similar to the new network applications such as cloud computing, the Internet of Things (IoT), the mobile Internet, and big data technology attract research interest based on computer and network advancements. However, the research on big data-driven online media public comment is still in the initial stage, and the relevant analysis model and its implementation plans remain to be further clarified. In this context, this study is put forward to clarify the dimensional model of network media public comment information based on big data and its action mechanism, and then express the implementation plans of the network media public comment analysis model based on big data. The model includes information collection technology, text clustering technology, and information preprocessing technology. The research results of this work is helpful to efficiently mine and identify the public comment information from the massive data in the era of big data and is referable for the public comment supervision and guidance in the network media.
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