I use latent semantic analysis (LSA) to extract synonyms from a large corpus of news articles. I was very happy with Gensim‘s LSA function, but I was not sure how to do LSA in R as good as in Python. There is an R package called lsa, but it is unsuitable for large matrices, because […]
Workshop on text analysis at ESSCE in London
I and Ken Benoit will convene a half-day workshop at European Symposium Series on Societal Challenges in Computational Social Science in November. We will explain how quanteda can be allied to different types of textual data in dictionary-based analysis. The material for the workshop contains the most updated examples.
Applying LIWC dictionary to a large dataset
LIWC is a popular text analysis package developed and maintained by Pennebaker et al. The latest version of the LIWC dictionary was released in 2015. This dictionary seems more appropriate than classic dictionaries such as the General Inquire dictionaries for analysis of contemporary materials, because our vocabulary changes over years. However, LIWC did not work […]
Presentation on my PhD thesis at departmental event
I presented my PhD thesis titled “Measuring News Bias in Complex Media Systems: A New Approach to Big Media Analysis” in a departmental event on the 9th June.
Workshops on Japanese text analysis using quanteda
I have presented how to analyze Japanese texts using quanteda in half-day workshops at Waseda University (22 May) and Kobe University (2 June) organized by Mikihito Tanaka (Waseda) and Atshushi Tago (Kobe). Materials for these workshops are made available on Github as Introduction to Japanese Text Analysis (IJTA).
quantedaによる日本語テキスト分析入門
quantedaについてのワークショップを早稲田大学で行いました。資料はRによる日本語テキスト分析入門と題して公開し、今後少しずつ内容を充実させていきます。今後、積極的に日本語テキストについてのワークショップの開催していこうと思うので、興味のある方はご連絡ください。
Upcoming presentation at Waseda University
I am invited to present a new approach to comparative text analysis in a research seminar at Waseda Universtiy (Tokyo) on 17th. My talk is titled Data-driven approach to bilingual text analysis: representation of US foreign policy in Japanese and British newspapers in 1985-2016. Kohei Watanabe will present a new approach to text analysis of […]
Redefining word boundaries by collocation analysis
Quanteda’s tokenizer can segment Japanese and Chinese texts thanks to stringi, but its results are not always good, because its underlying function, ICU, recognizes only limited number of words. For example, this Japanese text “ニューヨークのケネディ国際空港” can be translated to “Kennedy International Airport (ケネディ国際空港) in (の) New York (ニューヨーク)”. Quanteda’s tokenizer (tokens function) segments this into […]
Analyzing Asian texts in R on English Windows machines
R is generally good with Unicode, and we do not see garbled texts as far as we use stringi package. But there are some known bugs. The worst is probably the bug that have been discussed on the online community. On Windows, R prints character vectors properly, but not character vectors in data.frame: > sessionInfo() […]
R and Python text analysis packages performance comparison
Like many other people, I started text analysis in Python, because R was notoriously slow. Python looked like a perfect language for text analysis, and I did a lot of work during my PhD using gensim with home-grown tools. I loved gensim’s LSA that quickly and consistently decomposes very large document-feature matrices. However, I faced […]