Pattern for Python

By Tom De Smedt, Walter Daelemans. Journal of machine learning research, 2012

426 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/10ee4bfd16c2784adf54703daa24c37520fda1f3

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Citations in the corpus

Do not blame it on the algorithm: an empirical assessment of multiple recommender systems and their impact on content diversity (2018, unknown): “We estimated the polarity and subjectivity of the articles using the package Pattern (De Smedt & Daelemans, 2012).”
Computationally Detecting and Quantifying the Degree of Bias in Sentence-Level Text of News Stories (2015, unknown): “en module is a natural language processing (NLP) toolkit that leverages WordNet to score subjectivity according to the English adjectives used in the text [12].”
Evaluating and understanding text-based stock price prediction models (2014, methodology): “The average score of adjectives in each review was then compared to the original star rating, with a precision of 72% and a recall of 82% (De Smedt & Daelemans, 2012b).”
Adversarial Over-Sensitivity and Over-Stability Strategies for Dialogue Models (2018, methodology): “add a heuristic where an inflected verb is replaced with its respective infinitive form, and a plural noun with its singular form using the Pattern package (Smedt and Daelemans, 2012).”
External validity of sentiment mining reports: Can current methods identify demographic biases, event biases, and manipulation of reviews? (2014, methodology): “Analyzing this text with sentiment mining tool Pattern [6] shows that the review is 0.”
Using APIs for Data Collection on Social Media (2014, unknown): “… to open source tools, many research groups at universities are developing their own tools and platforms (e.g., Pattern at the University of Antwerp (De Smedt and Daelemans 2012); Digital Footprints at Aarhus University (Bechmann and Vahlstrup 2013), and…”
VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text (2014, methodology): “Pattern is a web mining module for Python , and the Pattern.en module is a natural language processing (NLP) toolkit (De Smedt & Daelemans, 2012) that leverages WordNet to score sentiment according to the English adjectives used in the text.”