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MixedEmotions
Documentation for the MixedEmotions Toolboxknowledge-graph
Creates knowledge graph from information processed by "Entity Extraction and Linking" module, and "Emotion Recognition from Text" moduleup_emotions_audio
This module aims to extract emotions from audio. The input argument is either an uploaded audio/video file to the server or a URL. The output is the predicted emotion in terms of Arousal and Valence within the JSON-LD format.twitter_crawlers
MixedEmotions module that connects to the Twitter Stream API in order to retrieve Tweets regarding certain keywords or phrasesbut_sentiment
Java wrapper around several sentiment analysis tools, that was created for MixedEmotions project, created by BUT.JSON-LD_schema
JSON-LD based format for representation of emotion, sentiment, entities and other results of language analysis in the MixedEmotions project.13_topic_extraction
Topic extraction service.entity-linking
Orchestrator
An example orchestrator to interact with the MixedEmotions' modules.NUIG-suggestion
Predicts whether a given text contains a suggestion or not. Given text can be a tweet or a sentence.05_emotion_hashtags_nuig
marathon_configurations
Marathon configuration files for the different MixedEmotions modules that have been dockerized and uploaded to MixedEmotions' Dockerhub.27_emotion_video_dcu
05_emotion_wassa_nuig
projectManager
Example for executing MixedEmotions' orchestratorNUIG-sentiment
A python based sentiment predictor for tweets. Uses LSTM and pre-trained embeddings.08_entity_extraction_es
Service for entity extractionLove Open Source and this site? Check out how you can help us