May 2018
Intermediate to advanced
228 pages
4h 11m
Japanese
Content preview from Rによるテキストマイニング ―tidytextを活用したデータ分析と可視化の基礎
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192
■
9
章 ケーススタディ：
Usenet
テキストの分析
図9-5 個々のUsenetニュースグループの各トピックに対するγ
文学のテキストを分析したときと同じように、トピックモデリングはラベルがな
くてもテキストに含まれるトピックを探し出すことに成功しています。
ただし、
Usenet
メッセージの分類は、ほかのトピックに対して高い γ値を示す
メッセージが多数含まれており、文学書を章に分けたときと比べてきれいに分類で
きているわけではありません。多くのメッセージが短く、頻出語に重なる部分があ
るので（たとえば、宇宙旅行と電子工学の議論には、共通して含まれる単語が多数
あるはずです）、これは意外なことではないでしょう。これは
LDA
がある程度の重
なり合いを認めながら文書をおおよそのトピックに分類することを示すリアルな例
です。
9.3
センチメント分析
第
2
章で説明したセンチメント分析のテクニックを使えば、これらの
Usenet
グ
ループへの投稿にポジティブな単語、ネガティブ
な単語がどれくらいの頻度で現れ
るかを調べられます。最もポジティブ、あるいはネガティブなニュースグループは
どれでしょうか。
この例では、個々の単語に数値のスコアを与える
AFINN
センチメント辞書を使っ
9.3
センチメント分析
■
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.