- Home
- Text Analytics Software
- TextAnalyzer
TextAnalyzer
What it is
TextAnalyzer is a free web tool for researchers analyzing English text. Upload a CSV or XLSX file with an ID column followed by a text column; other columns are ignored. It uses the NLTK tokenizer and open-source lexica to produce a tabular results file with a score column for each category. Available measures include Flesch-Kincaid grade level, concreteness, familiarity, emotionality, and pronoun frequencies. Its NRC Hashtag Emotion and Sentiment lexicon covers eight emotions—anger, anticipation, disgust, fear, joy, sadness, surprise, and trust—as well as positive and negative sentiment. TextAnalyzer can also compute topic models using latent Dirichlet allocation. An optional Age & Gender lexicon generates predictions about the text author’s age and gender. The tool is provided by Jonah Berger, Garrick Sherman, and Lyle Ungar of the University of Pennsylvania, and was founded in 2020. Its Free plan costs nothing. Comments, suggestions, and bug reports can be sent to [email protected].
For and against
For
- Free plan costs nothing.
- Analyzes text features including readability and pronoun frequencies.
- Computes topic models with latent Dirichlet allocation.
- Offers an optional Age & Gender lexicon.
Against
- Accepts English-language text.
- Input must be a CSV or XLSX file with ID and text columns.
The verdict
TextAnalyzer brings several lexicon-based measures and topic modeling together in a web tool for researchers. Its English-text focus and required file format are worth considering before preparing an analysis.
Who it suits
It suits researchers who want lexical, sentiment, emotion, or topic analyses of English text. Users need to supply CSV or XLSX files in the accepted column format.
Plans and prices
Free
Free NLP tools for researchers · CSV or XLSX text upload
Read 8 Oct 2026 · textanalyzer.org
On the record
- Demographics
- An optional Age & Gender lexicon produces predictions about a text author’s age and gender.textanalyzer.org · read 8 Oct 2026
- Input format
- The analyzer accepts CSV or XLSX files with an ID column followed by a text column; additional columns are ignored.textanalyzer.org · read 8 Oct 2026
- Lexical analysis
- The tool combines open source lexica to run lexical analyses on uploaded text.textanalyzer.org · read 8 Oct 2026
- Maker
- The resource is provided by Jonah Berger, Garrick Sherman, and Lyle Ungar of the University of Pennsylvania.textanalyzer.org · read 8 Oct 2026
- Processing
- Uploaded text is tokenized with the NLTK tokenizer, and results are returned as a tabular data file with a score column for each lexicon category.textanalyzer.org · read 8 Oct 2026
- Purpose
- TextAnalyzer provides NLP tools for researchers to analyze text data.textanalyzer.org · read 8 Oct 2026
- Sentiment and emotion
- The NRC Hashtag Emotion and Sentiment lexicon covers anger, anticipation, disgust, fear, joy, sadness, surprise, trust, and positive and negative sentiment.textanalyzer.org · read 8 Oct 2026
- Support
- Comments, suggestions, and bug reports can be sent to [email protected].textanalyzer.org · read 8 Oct 2026
- Supported language
- The about page describes the input as English language text.textanalyzer.org · read 8 Oct 2026
- Text features
- Available text features include Flesch-Kincaid grade level, concreteness and familiarity, emotionality, and pronoun frequencies.textanalyzer.org · read 8 Oct 2026
- Topic modeling
- The tool computes topic models using latent Dirichlet allocation.textanalyzer.org · read 8 Oct 2026
