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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■
15
2
章
整理データを使った
センチメント分析
前章では、整理テキスト形式とはどういうことであるかを探究し、単語の出現頻
度の問題を解くためにこの形式がどのように利用できるかを示しました。これを使
うことで、文書に含まれる最頻出語はどれかを分析し、また文書を比較しました。
しかし、この章では話題を変え、意見マイニング（
opinion mining
）あるいはセンチ
メント分析（
sentiment analysis
）について考えることにします。文章を読むとき、人
は言葉が持つ感情的（センチメント）な意図について、ポジティブなものかネガティ
ブなものか、驚きとか嫌悪感といったもっと微妙な意味合いを持つ言葉で表現すべ
きものかといったことを推論します。図 2-1 に示すように、テキストマイニングの
ツールを使えば、プログラムを通じてテキストに含まれる感情的な要素にアプロー
チできます。
整理テキスト
テキスト
集計データ
テキスト
データ
可視化
センチメント
辞書
inner_join
dplyr
group_by
summarize
dplyr
unnest_tokens
tidytext
count
dplyr
ggplot2
dplyr, tidyr
dplyr, tidyr
図2-1 tidytextを使ってセンチメント分析を行う典型的なテキスト分析のフローチャート
テキストのセンチメント分析の方法の
1
つは、テキストを個別の単語の組み合わ
せと考え、テキスト全体の感情内容は個別の単語の感情内容の総和と考えるもので
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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.