Qiita記事のタグ傾向の調査

# はじめに
最近Qiita記事にお世話になる（技術参考にさせていただく）ことが多くなり、記事数が多いタグがトレンドなのだろうと盲目的に思っていた。しかし、それは本当なのだろうかとふと疑問が湧いてきた。
Qiitaには無料で利用できるAPIが提供されているため、それを活用して検証してみようと思う。

# 結果
PythonやAWSなどの上位タグは、最新投稿でも多く使われる傾向があった。
しかしながら、ChatGPTのようなトレンドであるタグは上位タグには出現していないことが明らかになった。
上位タグは飽く迄も累積値であり、直近タグ付けされた件数（トレンド）とはイコールにはならない結果となった。
上位10位を下表に示す。
<img src="https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/2820631/18ac3b01-430f-3681-5121-b1ac3748ee81.png" width=60%>

# 利用した技術
**Qiita API**
・GET /api/v2/tags
 　タグされている記事数を得られるAPI
　　API例）`https://qiita.com/api/v2/tags?page=1&per_page=100&sort=count`
・GET /api/v2/items
　記事の一覧を得られるAPI
　　API例）`https://qiita.com/api/v2/items?page=1&per_page=100`
Qiita APIの仕様は以下を参照。
<a href="https://qiita.com/api/v2/docs">Qiita API v2ドキュメント - Qiita:Developer</a>

**Node-RED**
Node-REDのフロー図は以下。
<img src="https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/2820631/b9ed63b2-f5ef-6b42-fcc2-2d60ed5b5f32.png" width=80%>

```JSON:iv.JSON
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```

# おわりに
以下に課題を記載する。
・今回、最新投稿の500件を対象としたが、母数を多くすることで分析の精度を上げたい
・APIから取得したデータの整形、集計、分析に手作業が多く、効率化を図りたい