virallab.github.io/resources.html at main · ViralLab/virallab.github.io · GitHub

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                        <h5 class="card-title">TurkishBERTweet</h5>
                        <p class="card-text">TurkishBERTweet is the first large-scale pre-trained language model
                            specifically designed for Turkish social media. Built using over 894 million Turkish tweets,
                            it shares the architecture of the RoBERTa-base model but is optimized for social media
                            content. TurkishBERTweet excels in tasks like Sentiment Classification and Hate Speech
                            Detection, offering better generalizability and lower inference times compared to existing
                            models.</p>
                        <p class="card-text"><small class="text-body-secondary">
                                <a href="https://varollab.com/TurkishBERTweet/" target="_blank">🌐
                                    varollab.com/TurkishBERTweet</a>
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                        <h5 class="card-title">Social Media Data Toolkit</h5>
                        <p class="card-text">SMDT (Social Media Data Toolkit) is a comprehensive Python library designed
                            to streamline the ingestion, standardization, and analysis of social media data. It provides
                            a unified interface for handling data from diverse platforms, enabling researchers to focus
                            on analysis rather than data wrangling.</p>
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                                <a href="https://varollab.com/SMDT" target="_blank">🌐
                                    varollab.com/SMDT</a>
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                        <h5 class="card-title">Secim 2023</h5>
                        <p class="card-text">This platform shares data science insights and reports from our
                            disinformation and coordinated activity detection project on upcoming 2023 Turkish
                            Presidential Election. The platform offers several interactive tools to invesitage anomalous
                            followers and timeseries patterns.</p>
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                                <a href="https://secim2023.biz/" target="_blank">🌐 secim2023.biz</a>
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                        <h5 class="card-title">Interactive Scientific Interaction Visualization</h5>
                        <p class="card-text">This is a tool developed to visualize various academic networks. Core
                            framework applied for different datasets and academic groups listed below.</p>
                        <p class="card-text"><small class="text-body-secondary">
                                <a href="https://onurvarol.com/hcss" target="_blank">🌐
                                    Handbook of Computational Social Sciences</a>
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                            <small class="text-body-secondary">
                                <a href="https://onurvarol.com/bagep" target="_blank">🌐
                                    Science Academy BAGEP Awardees Network</a>
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                            <small class="text-body-secondary">
                                <a href="https://www.onurvarol.com/sosyal-veri-bilimi/" target="_blank">🌐
                                    Sosyal Veri Bilimi kitabı yazar ağı</a>
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