emotions

A matrix containing words (n = 175,592) and the emotion category most frequently associated with each word.
This dataset is a modified version of the 'DepecheMood++' lexicon developed by
Araque, Gatti, Staiano, and Guerini (2018). For proper scoring, text should not be
stemmed prior to using this lexicon. This version of the lexicon does not
rely on part of speech tagging.

datasets

Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.

Aleksandar Tomašević

transforEmotion

Sentiment Analysis for Text, Image and Video using Transformer
Models

Alexander Christensen

Hudson Golino

emotions function

A data frame with 175,592 rows and 9 columns.<dl>
 <dt>word</dt>
<dd>An entry in the lexicon, in English</dd> <dt>AFRAID, AMUSED, ANGRY, ANNOYED, DONT_CARE, HAPPY, INSPIRED, SAD</dt>
<dd>The emotional category. All emotions contain either a 0 or 1. If the
 category is most likely to be associated with the word, it recieves a 1, otherwise, 0.
 Words are only associated with one category.</dd>
</dl>

Format

Emotions Data — emotions

A data frame with 175,592 rows and 9 columns.<dl>
 <dt>word</dt>
<dd>An entry in the lexicon, in English</dd>

 <dt>AFRAID, AMUSED, ANGRY, ANNOYED, DONT_CARE, HAPPY, INSPIRED, SAD</dt>
<dd>The emotional category. All emotions contain either a 0 or 1. If the
 category is most likely to be associated with the word, it recieves a 1, otherwise, 0.
 Words are only associated with one category.</dd>


</dl>

emotions: Emotions Data

Description

Usage

Arguments

Format

References

Examples