Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data

在这个小项目中，我选择对推特和Reddit等社交媒体网站进行情感分析，以深入了解人们对2019年下议院选举总理候选人的看法。社交媒体为人们在任何地方、任何时间表达个人、事件或话题的看法提供了平台，也是最简单、最快捷的方式。因此，分析这些情绪对于了解热门话题以及人们对这些话题的情绪等方面将非常有用。该小项目还旨在实现和比较现代机器学习文本分类算法，以预测文本的情感。

  • 语言Jupyter Notebook
  • 大小40.8 MB
  • 更新2020年3月5日
在 GitHub 打开
avatarchaithanya21
12
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项目介绍

chaithanya21/Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data 是一个托管在 GitHub 上的开源项目，主要使用 Jupyter Notebook 编写，目前获得 12 个 Star、2 次 Fork。

仓库全名
chaithanya21/Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data
Star 数
12
Fork 数
2

README 摘要

Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data In this mini-project i have chosen to do sentiment analysis of social media websites such as twitter and reddit to gain insights into the people’s opinion towards prime ministerial candidates for the Lok Sabha election 2019. Social media provides a platform for people’s opinion of a person or event or topic to be heard from anywhere at any time and is the…

完整内容见 GitHub 原始 README 或本页 。

常见问题

Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data 用什么语言开发？

主要使用 Jupyter Notebook 编写，目前有 12 个 Star。

如何获取 Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data 的源码？

可以直接克隆仓库：git clone https://github.com/chaithanya21/Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data.git；安装与运行步骤见仓库 README。

Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data 最近还在维护吗？

仓库最近一次更新为 2020年3月5日，当前没有未关闭的 Issue；Star 数为 12，可作为社区活跃度的参考。

本页面展示项目元数据与原始 README，GitRead 中文社区 编辑团队负责选题收录。

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关于

GitHub 原始描述（英文）

In this mini-project i have chosen to do sentiment analysis of social media websites such as twitter and reddit to gain insights into the people’s opinion towards prime ministerial candidates for the Lok Sabha election 2019. Social media provides a platform for people’s opinion of a person or event or topic to be heard from anywhere at any time and is the easiest and fastest way for them to do it. So, analysing these sentiments will be of immense use in knowing the trending topics and the mood of the people towards those topics among other things. The mini-project also aims at implementing and comparing contemporary machine learning text classification algorithms to predict the sentiment of a piece of text.

描述取自 GitHub 官方 API，保持仓库作者书写的原文。

简要分析

热度分
28
价值分
9
活跃状态
活跃
anaconda-distributionexploratory-data-analysismachine-learningnatural-language-processingpysparkpython3sentiment-analysissocial-media
GitHub

语言占比

Jupyter Notebook

贡献者

chaithanya21chaithanya21

README

Sentiment-Analysis-using-Pyspark-on-Multi-Social-Media-Data

In this mini-project i have chosen to do sentiment analysis of social media websites such as twitter and reddit to gain insights into the people’s opinion towards prime ministerial candidates for the Lok Sabha election 2019. Social media provides a platform for people’s opinion of a person or event or topic to be heard from anywhere at any time and is the easiest and fastest way for them to do it. So, analysing these sentiments will be of immense use in knowing the trending topics and the mood of the people towards those topics among other things. The mini-project also aims at implementing and comparing contemporary machine learning text classification algorithms to predict the sentiment of a piece of text.

Use jupyter Notebooks or Anaconda Distribution to open all the .ipynb files. Do not open the files directly

Download the Entire Dataset From the Below Link

Kaggle Datasets

Additional Information with complete Source Code Implementation

Medium:Sentimental Analysis On Multi Source Social Media Data Using Pyspark

'ML'

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