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As a beginner text-miner, I really want to ask for advices/guidelines on graph mining, based on a real need of me: build a keyword-related graph from an initial input keyword.

I know the topic is relatively large, so I want to do it for Twitter first: I have harvested a tweet corpus of the keywords "survey" and "market". I want to mine from that corpus to build a graph of keywords related to "survey" or "market".

I have tried using NodeXL and NLTK but I couldn't do what I want.

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我不太确定你的目标是什么，但这里有一些建议。
对于可以构建的图形类型，您有多种选择。

  • 您可以构建一个二分图，一侧是推文，另一侧是关键词。
  • 你可以建立一个网络，其中顶点是推文，边代表一个通用术语
  • 或者您可以构建一个网络，其中顶点是关键字，边表示关键字出现在同一条推文中
这一切都取决于你试图发现什么。

查看http://www.kdnuggets.com/websites/twitter-analytics-data-mining.html获取一些建议

IEEE 和/或 ACM 还发表了许多关于 Twitter 的基于图的挖掘的优秀论文

于 2012-11-06T04:53:23.090 回答