TE
科技回声
首页24小时热榜最新最佳问答展示工作
GitHubTwitter
首页

科技回声

基于 Next.js 构建的科技新闻平台,提供全球科技新闻和讨论内容。

GitHubTwitter

首页

首页最新最佳问答展示工作

资源链接

HackerNews API原版 HackerNewsNext.js

© 2025 科技回声. 版权所有。

Analyzing stylistic similarity amongst authors

37 点作者 lingben将近 10 年前

2 条评论

mirimir将近 10 年前
This is very cool work! Some years ago, I was interested in text mining. I ended up playing with latent semantic analysis using Lucene etc. But that was a largely random choice, driven by the availability of open-source software and online discussion.<p>However, as cool as stylistic analysis is, I&#x27;m concerned about implications for online anonymity (which I consider valuable). But maybe the risk is limited by typical text length and false positive rate. I welcome suggestions for further reading.
nicolewhite将近 10 年前
Very cool. I wonder why the author decided to use igraph within R instead of Python, as he was already using Python for the frequencies.
评论 #10051222 未加载