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SenpySenpy is a framework to build sentiment and emotion analysis services. It provides functionalities for developing developing sentiment and emotion classifier and exposing them as an HTTP service and for evaluating sentiment algorithms with well known datasets. If you want to use Senpy in your research, please cite
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Senpy Chrome Plugin for Analyzing Sentiment and Emotions in TextsChrome Plugin for Analyzing Sentiment and Emotion in Texts.It provides a Asimple way to analyse any text on any web page and obtain instant information about it. You can customize the experience and use the different plugins available to obtain different results. The results can be shown in charts and in the selected text, using dynamic colour styling of the sentences. |
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Participation Chrome Plugin for Detecting RadicalizationChrome Plugin for Detecting Radicalization and Emotion in Texts.It provides a simple way to analyse any text on any web page and obtain instant information about it. You can customize the experience and use the different plugins available to obtain different results. The results can be shown in charts and in the selected text, using dynamic colour styling of the sentences. |
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GSI CrawlerGSI Crawler is an innovative and useful framework which aims to extract information from web pages enriching following semantic approaches. At the moment, there are three available platforms: Twitter, Reddit and News. The user interacts with the tool through a web interface, selecting the analysis type he wants to carry out and the platform that is going to be examined |
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EwetaskerEwetasker is an emotion aware automation platform based on semantic ECA (Event-Condition-Action) rules. It is capable of enable semantic automation rules in a smart environment allowing the user to configure his own automation rules in an easy way |
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SOILSoil is an Agent-based Social Simulator in Python focused on Social Networks.. |
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SematchSematch is an integrated framework for the development, evaluation and application of semantic similarity for Knowledge Graphs. It focuses on knowledge-based semantic similarity that relies on structural knowledge in a given taxonomy (e.g. depth, path length, least common subsumer), and statistical information contents. Researchers can use Sematch to develop and evaluate semantic similarity metrics and exploit these metrics in applications. |
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SefaradSefarad is an environment developed to explore, analyse and visualize data. Sefarad framework has multiple predefined dashboards which are ready to be used. Due to its high flexibility, it enables to display any kind of information, either user custom data sets or others included by default in the project. |
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GSITKGsitk is a library on top of scikit-learn that eases the development process on NLP machine learning driven projects. It uses numpy, pandas and related libraries to easy the development. |
