docker gsi-crawler


Senpy 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



github gsi-crawler docker gsi-crawler

GSI Crawler

GSI 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


docker gsi-crawler


Ewetasker 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

gitlab soil github gsi-crawler


Soil is an Agent-based Social Simulator in Python focused on Social Networks..

If you use Soil in your research, do not forget to cite this paper.


docker gsi-crawler


Sematch 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.



Sefarad 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.



Gsitk 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.

If you use gsitk in your research, please cite.



github gsi-crawler



Stylomepy is a Python library for measuring the style of a text.
It can be used in the analysis of the statistics of a text, the readability index of it, the vocabulary richness, formality and coherence