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"As the web is becoming ubiquitous, interactive, and multimodal, technology needs to deal increasingly with human factors, including emotions. The present draft specification of Emotion Markup Language 1.0 aims to strike a balance between practical applicability and scientific well-foundedness. The language is conceived as a "plug-in" language suitable for use in three different areas: (1) manual annotation of data; (2) automatic recognition of emotion-related states from user behavior; and (3) generation of emotion-related system behavior."

"The Sentikator is a computer linguistic engine designed to calculably recognize, analyze and quantify emotions and content in texts. It allows extracting sentiment out of news, analyst recommendations, social media data, transcripts, press releases, broker news, factsheets, weather forecasts and many other sources. Sentiment extraction is highly reliable and disseminated data is preprocessed so that implementation into existing or new financial applications is easily possible. The Sentikator gives valuable insights to emotions"

"Using natural language processing, TransProse reads in text and determines densities of eight different emotions (joy, sadness, anger, disgust, anticipation, surprise, trust, and fear) and two different states (positive or negative) throughout the novel. The musical piece chronologically follows the novel. It uses the emotion density data to determine the tempo, key, notes, octaves, etc. for the piece depending on different rules and parameters. The pieces are available for download at "

She as a woman / down her loneline / and emotional child (.....)