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#textanalysis

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Nick Byrd, Ph.D.<p>Wow! <a href="https://nerdculture.de/tags/QualiService" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>QualiService</span></a> could be a great resource!</p><p>It wasn't obvious to me how to find the transcripts for these doctor-patient interaction data from 4 countries, but if such transcripts are accessible, that's GREAT!</p><p><a href="https://www.qualiservice.org/en/qsearch.html?q=diagnosis" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">qualiservice.org/en/qsearch.ht</span><span class="invisible">ml?q=diagnosis</span></a></p><p><a href="https://nerdculture.de/tags/medicine" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>medicine</span></a> <a href="https://nerdculture.de/tags/openData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openData</span></a> <a href="https://nerdculture.de/tags/cogSci" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cogSci</span></a> <a href="https://nerdculture.de/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a></p>
Mario Angst<p>🇪🇺 Want to analyze text from the EU public consultations? EU public consultations are a way in which the EU invites the broader public to publicly comment on upcoming legislation.</p><p>📦 :python: I just published a first version of a Python package {eu-consultations} to scrape and extract text from the EU website: <br><a href="https://github.com/marioangst/eu_consultations" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/marioangst/eu_consu</span><span class="invisible">ltations</span></a></p><p>- download consultation data as displayed on the EU's frontend into a validated form<br>- download associated files (this is the hard part about analysing this data - lots of feedback is in .docx and .pdf files)<br>- extract text from the files using docling and attach to feedback</p><p>You get all data in validated form and possibly stored in huge (sorry for that) JSON files ;).</p><p>This package is part of an analysis project on feedback the EU has received via the public consultation process on digital policy we plan to present later this year, but I thought let's make some of the tools we use open source way earlier already.</p><p><a href="https://fediscience.org/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a> <a href="https://fediscience.org/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://fediscience.org/tags/policyanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>policyanalysis</span></a> <a href="https://fediscience.org/tags/CompSocSci" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CompSocSci</span></a></p>
George Macgregor<p>Useful contribution to discussions in this area, for sure! The results highlight "whether an automated approach that would still require micromanaging and adjusting several variables by the human researcher would, in fact, be more efficient an approach compared to the same tasks performed manually by human labour"</p><p>Out of Context! Managing the Limitations of Context Windows in <a href="https://code4lib.social/tags/ChatGPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatGPT</span></a>-4o Text Analyses <a href="https://doi.org/10.46298/jdmdh.15090" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.46298/jdmdh.15090</span><span class="invisible"></span></a> <a href="https://code4lib.social/tags/DigitalHumanities" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DigitalHumanities</span></a> <a href="https://code4lib.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://code4lib.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a> <a href="https://code4lib.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://code4lib.social/tags/GLAMR" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GLAMR</span></a></p>
khushnuma<p>NLP for Data Science: Insights from Text</p><p><a href="https://mastodon.social/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.social/tags/NaturalLanguageProcessing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NaturalLanguageProcessing</span></a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.social/tags/DataMining" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataMining</span></a> <a href="https://mastodon.social/tags/BigData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BigData</span></a> <a href="https://mastodon.social/tags/TextMining" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextMining</span></a> <a href="https://mastodon.social/tags/SentimentAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SentimentAnalysis</span></a> <a href="https://mastodon.social/tags/TopicModeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TopicModeling</span></a> <a href="https://mastodon.social/tags/WordEmbeddings" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WordEmbeddings</span></a> <a href="https://mastodon.social/tags/DataVisualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataVisualization</span></a> </p><p><a href="https://pando.life/article/256881" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">pando.life/article/256881</span><span class="invisible"></span></a></p>
khushnuma<p>Why Natural Language Processing (NLP ) Is the Future of Data Science</p><p><a href="https://mastodon.social/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.social/tags/BigData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BigData</span></a> <a href="https://mastodon.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://mastodon.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.social/tags/NaturalLanguageProcessing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NaturalLanguageProcessing</span></a> <a href="https://mastodon.social/tags/DataAnalytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataAnalytics</span></a> <a href="https://mastodon.social/tags/DataMining" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataMining</span></a> <a href="https://mastodon.social/tags/LanguageModels" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LanguageModels</span></a> <a href="https://mastodon.social/tags/PredictiveAnalytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PredictiveAnalytics</span></a> <a href="https://mastodon.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://mastodon.social/tags/DataVisualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataVisualization</span></a> <a href="https://mastodon.social/tags/DataDriven" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataDriven</span></a> <a href="https://mastodon.social/tags/TechInnovation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechInnovation</span></a> <a href="https://mastodon.social/tags/Analytics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Analytics</span></a> <a href="https://mastodon.social/tags/SmartTech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SmartTech</span></a> <a href="https://mastodon.social/tags/FutureOfAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FutureOfAI</span></a></p><p><a href="https://icacedu.com/why-a-natural-language-processing-nlp-is-the-future-of-data-science/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">icacedu.com/why-a-natural-lang</span><span class="invisible">uage-processing-nlp-is-the-future-of-data-science/</span></a></p>
khushnuma<p>Mastering these core NLP techniques is crucial for any data scientist dealing with text data. From tokenization to language modeling, each method serves a unique purpose in processing, analyzing, and extracting valuable insights from textual information.</p><p><a href="https://mastodon.social/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.social/tags/Tokenization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Tokenization</span></a> <a href="https://mastodon.social/tags/LanguageModeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LanguageModeling</span></a> <a href="https://mastodon.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://mastodon.social/tags/TextMining" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextMining</span></a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> </p><p>read more: <a href="https://blogulr.com/khushnuma7861/topnlptechniqueseverydatascientistshouldknow-120682" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">blogulr.com/khushnuma7861/topn</span><span class="invisible">lptechniqueseverydatascientistshouldknow-120682</span></a></p>
Nick Byrd, Ph.D.<p>Like we found in “Your Health vs. My Liberty” (<a href="https://doi.org/10.1016/j.cognition.2021.104649" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1016/j.cognition.20</span><span class="invisible">21.104649</span></a>) Yael Rozenblum et al. found that compliance with <a href="https://nerdculture.de/tags/publicHealth" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>publicHealth</span></a> guidance correlated with indicators of the perceived threat of a viral pandemic.</p><p>Also, relying on <a href="https://nerdculture.de/tags/misinformation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>misinformation</span></a> correlated with reliance on simple (vs. complex) <a href="https://nerdculture.de/tags/reasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reasoning</span></a>.</p><p>The free paper: <a href="https://doi.org/10.1002/tea.21975" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.1002/tea.21975</span><span class="invisible"></span></a></p><p><a href="https://nerdculture.de/tags/medicine" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>medicine</span></a> <a href="https://nerdculture.de/tags/health" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>health</span></a> <a href="https://nerdculture.de/tags/education" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>education</span></a> <a href="https://nerdculture.de/tags/psychology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychology</span></a> <a href="https://nerdculture.de/tags/epistemology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>epistemology</span></a> <a href="https://nerdculture.de/tags/logic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>logic</span></a> <a href="https://nerdculture.de/tags/textAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textAnalysis</span></a></p>
Daniela Schneider<p>Have you ever wanted to use a <a href="https://fedihum.org/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a> as one step in a workflow?</p><p>We integrated <a href="https://fedihum.org/tags/GPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPT</span></a> into the open-source analysis platform <a href="https://fedihum.org/tags/useGalaxy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>useGalaxy</span></a>, where you can link GPT to several thousand other tools, add more attachments for analysis and make your research reproducible. </p><p><a href="https://galaxyproject.org/news/2024-09-02-chat-gpt/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">galaxyproject.org/news/2024-09</span><span class="invisible">-02-chat-gpt/</span></a></p><p>In our example, we uploaded an audio file and used <a href="https://fedihum.org/tags/Whisper" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Whisper</span></a> to convert it into text, cut out the moderation, and prompted chatGPT to translate it into German. </p><p><a href="https://fedihum.org/tags/DH" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DH</span></a> <a href="https://fedihum.org/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://fedihum.org/tags/tools" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tools</span></a> <br><span class="h-card" translate="no"><a href="https://xn--baw-joa.social/@galaxyfreiburg" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>galaxyfreiburg</span></a></span></p>
Fabio Giglietto<p>📚🇮🇹 New working paper: "Evaluating Embedding Models for Clustering Italian Political News"</p><p>This study compares embedding models for unsupervised clustering of Italian political news shared on Facebook before the 2018 and 2022 elections, aiming to advance NLP methods for political text analysis in non-English languages.</p><p>Paper: <a href="https://osf.io/preprints/osf/2j9ed" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">osf.io/preprints/osf/2j9ed</span><span class="invisible"></span></a></p><p>Code &amp; data: <a href="https://github.com/fabiogiglietto/Semantic-Clustering-Italian-News" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/fabiogiglietto/Sema</span><span class="invisible">ntic-Clustering-Italian-News</span></a></p><p>Feedback welcome!</p><p><a href="https://aoir.social/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://aoir.social/tags/PoliticalScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PoliticalScience</span></a> <a href="https://aoir.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://aoir.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a></p>
Jason Robison<p>Pycpidr 0.3.0 introduces:<br>- Dependency-based Idea Density (DEPID)<br>- DEPID-R<br>- Custom sentence and token filters for DEPID</p><p>github.com/jrrobison1/pycpidr</p><p><a href="https://mastodon.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://mastodon.social/tags/Linguistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Linguistics</span></a> <a href="https://mastodon.social/tags/psychometrics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychometrics</span></a> <a href="https://mastodon.social/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://mastodon.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://mastodon.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://mastodon.social/tags/IdeaDensity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>IdeaDensity</span></a> <a href="https://mastodon.social/tags/Dementia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Dementia</span></a> <a href="https://mastodon.social/tags/alzheimers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alzheimers</span></a> <a href="https://mastodon.social/tags/ResearchTools" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ResearchTools</span></a></p>
Paul Houle<p>🎯 Potential terrorists can be identified from social media posts, new research shows</p><p><a href="https://phys.org/news/2024-08-potential-terrorists-social-media.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">phys.org/news/2024-08-potentia</span><span class="invisible">l-terrorists-social-media.html</span></a></p><p><a href="https://mastodon.social/tags/media" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>media</span></a> <a href="https://mastodon.social/tags/socialmedia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>socialmedia</span></a> <a href="https://mastodon.social/tags/privacy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>privacy</span></a> <a href="https://mastodon.social/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://mastodon.social/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a></p>
Jason Robison<p>Just launched: pycpidr 🎉<br><a href="https://github.com/jrrobison1/pycpidr" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/jrrobison1/pycpidr</span><span class="invisible"></span></a></p><p>Python library to determine the propositional idea density of an English text automatically. </p><p>Idea density is a measure of the amount of information conveyed relative to the number of words used. This metric has applications in various fields, including linguistics, cognitive science, and healthcare research.<br><a href="https://mastodon.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://mastodon.social/tags/Linguistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Linguistics</span></a> <a href="https://mastodon.social/tags/psychometrics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychometrics</span></a> <a href="https://mastodon.social/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://mastodon.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://mastodon.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a></p>
Elias Dabbas :verified:<p>Word co-occurrence matrix/heatmap</p><p>How to compute and visualize the correlation between terms that occur together in a list of documents*</p><p>*documents: keywords, page titles, product names/descriptions, social media posts, etc.</p><p><a href="https://bit.ly/3Z4tiTx" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">bit.ly/3Z4tiTx</span><span class="invisible"></span></a></p><p><a href="https://seocommunity.social/tags/DataVisualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataVisualization</span></a> <a href="https://seocommunity.social/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://seocommunity.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://seocommunity.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a></p>
Harald Klinke<p>The Digital Humanities Team at the University of Vienna and the Ottoman Nature in Travelogues (ONiT) project are hosting a <a href="https://det.social/tags/hackathon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hackathon</span></a> focused on analyzing texts, images, and multimodal sources.</p><p>Thursday, November 14, 9:00 CET to Friday, November 15, 15:00 CET<br><a href="https://dh.univie.ac.at/hackathon/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">dh.univie.ac.at/hackathon/</span><span class="invisible"></span></a><br><a href="https://det.social/tags/DigitalHumanities" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DigitalHumanities</span></a> <a href="https://det.social/tags/ComputationalHumanities" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalHumanities</span></a> <a href="https://det.social/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://det.social/tags/ImageAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageAnalysis</span></a></p>
Marshall A. Taylor<p>It was also a methodologically fun paper, combining digitized archival text, Census &amp; survey data, NLP, and panel models.</p><p>Email or dm me for a copy! <a href="https://sciences.social/tags/sociology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sociology</span></a> <a href="https://sciences.social/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://sciences.social/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a></p><p>3/3</p>
Paul Houle<p>😓 An NLP-Based System for Detecting Depression Levels through User Comments on Twitter (X)</p><p><a href="https://www.mdpi.com/2227-7390/12/13/1926" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">mdpi.com/2227-7390/12/13/1926</span><span class="invisible"></span></a></p><p><a href="https://mastodon.social/tags/mentalhealth" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mentalhealth</span></a> <a href="https://mastodon.social/tags/depression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>depression</span></a> <a href="https://mastodon.social/tags/nlp" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nlp</span></a> <a href="https://mastodon.social/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://mastodon.social/tags/socialmedia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>socialmedia</span></a> <a href="https://mastodon.social/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://mastodon.social/tags/privacy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>privacy</span></a></p>
Axel Pichler<p>📣 Attention Linguistics &amp; Digital Humanities students! 🎓📚<br>Join <span class="h-card" translate="no"><a href="https://fedihum.org/@janispagel" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>janispagel</span></a></span> and me for the »Prompting, Evaluation, Interpretation: An Introduction to LLMs in Text Analysis« course at the upcoming Deep Learning for Language Analysis Summer School in Cologne: <a href="http://ml-school.uni-koeln.de" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="">ml-school.uni-koeln.de</span><span class="invisible"></span></a>! 📝🔍<br>🗓️ Don't miss out – registration is open until June 16th! 🙌<br><a href="https://fedihum.org/tags/LLMs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLMs</span></a> <a href="https://fedihum.org/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a> <a href="https://fedihum.org/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a> <a href="https://fedihum.org/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://fedihum.org/tags/Linguistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Linguistics</span></a> <a href="https://fedihum.org/tags/DigitalHumanities" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DigitalHumanities</span></a> <a href="https://fedihum.org/tags/CRETA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CRETA</span></a></p>
R User Group @Harvard :rstats:<p>Want to learn more about how to use regular expressions in R?</p><p>Come join us to learn how to use regular expressions to parse and clean text data on Thursday, June 6th, 5-6pm Eastern Time!</p><p>Find the Zoom registration details on our website: </p><p><a href="https://rug-at-hdsi.org/upcoming_events/2024-05-06-regex-sarah-hirsch.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">rug-at-hdsi.org/upcoming_event</span><span class="invisible">s/2024-05-06-regex-sarah-hirsch.html</span></a> </p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://fosstodon.org/tags/regex" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>regex</span></a> <a href="https://fosstodon.org/tags/TextAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextAnalysis</span></a></p>
alissonmasoares<p>Bias estimation in word embeddings using a Bayesian approach instead of WEAT or MAC. A new paper in Computational Linguistics.</p><p><a href="https://fosstodon.org/tags/ComputationalSocialSciences" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalSocialSciences</span></a> <a href="https://fosstodon.org/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://fosstodon.org/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a></p>
🧿🪬🍄🌈🎮💻🚲🥓🎃💀🏴🛻🇺🇸<p>How would you go about creating a filter that blocks posts about things that people hate?</p><p>I've thought I could build a text classifier, but it could be hard to train since I'd need to guess whether or not the author hates the thing they are posting about.</p><p>I wouldn't want it to become a filter for all current events news, but I suspect that's what it would become.</p><p><a href="https://mastodon.social/tags/fediverse" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fediverse</span></a> <a href="https://mastodon.social/tags/mastodon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mastodon</span></a> <a href="https://mastodon.social/tags/machineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machineLearning</span></a> <a href="https://mastodon.social/tags/tfidf" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tfidf</span></a> <a href="https://mastodon.social/tags/classification" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>classification</span></a> <a href="https://mastodon.social/tags/socialMedia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>socialMedia</span></a> <a href="https://mastodon.social/tags/classifier" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>classifier</span></a> <a href="https://mastodon.social/tags/textAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textAnalysis</span></a> <a href="https://mastodon.social/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>programming</span></a> <a href="https://mastodon.social/tags/tech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tech</span></a> <a href="https://mastodon.social/tags/technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>technology</span></a></p>
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