Substance Use Stigma Detection System for Reddit Data (2022)
System that leverages contextual embeddings combined with affective, social, and behavioral features to classify instances of substance use stigma in Reddit posts.
System that leverages contextual embeddings combined with affective, social, and behavioral features to classify instances of substance use stigma in Reddit posts.
English and Arabic Twitter sarcasm detection systems. Group project for University of Washington 573: NLP Systems and Applications.
A GRU-based character-level language model trained on a corpus of the fiction of H.P. Lovecraft.
A Pytorch implementation of the Deep Averaging Network introduced in Iyyer et al (2015). Performs binary sentiment classification on the IMDB reviews dataset.
This code was created to classify a subset of the 20 newsgroups text dataset from sci-kit learn. Posts drawn from the ‘talk.politics.guns’, ‘talk.politics.mideast’, and ‘talk.politics.misc’ were converted to a bag of words representation, and classified using a ‘from scratch’ kNN implementation.
The script builds a decision tree ‘from scratch’ using the training data (a subset of the 20 newsgroups text dataset from sci-kit learn), classifies the training and test data, and calculates the accuracy.
This script reads an HMM file produced by the MALLET machine learning toolkit and uses an implementation of the Viterbi algorithm to find the most probable tag sequence for the text.
A ‘from scratch’ naive Bayes classifier implementation that classifies fragments of text according to language category.
A search trie implementation that locates DNA sequences in the human genome chromosome dataset produced by UCSC.
Master's thesis, Portland State University, 2020
This thesis documents the development of the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers.
Recommended citation: Roesler, D. (2020). A computer science academic vocabulary list [Master's thesis, Portland State University]. https://doi.org/10.15760/etd.7414
Journal of English for Academic Purposes, 2021
This article presents the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers.
Recommended citation: Roesler, D. (2021). When a bug is not a bug: An introduction to the Computer Science Academic Vocabulary List, Journal of English for Academic Purposes, 101044. https://doi.org/10.1016/j.jeap.2021.101044
under review, 2022
Using an annotated Reddit corpus, we train a set of binary classifiers, in which each classifier detects one of three substance use stigma types: Internalized Stigma, Anticipated Stigma, and Enacted Stigma. By combining RoBERTa contextual embeddings and affective, social, and behavioral features, we produce systems that identify instances of substance use stigma for all three stigma types and outperform RoBERTa-only baselines by up to 6.45 macro F1.
Recommended citation: TBA https://github.com/droesler/droesler.github.io/blob/master/files/stigma_paper_preprint_12_15_2022.pdf
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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