OpenML
Emotions--Sensor-Data-Set

Emotions--Sensor-Data-Set

active ARFF Database: Open Database, Contents: Original Authors Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context Emotions Detection Is an Interesting Blend of Psychology and Technology. -This Technology Helps to Build a Companion Robots,This Robots Can be Friendly and Have The Ability to Recognize Users Emotions and Needs, and to Act Accordingly. -Its Essentially a Way to Determine How your Consumers are Reacting to Your Website, Social Media Posts, and Other Forms of Your Online Content This Helps to Transform the Face of Marketing and Advertising by Reading Human Emotions and Then Adapting Consumer Experiences to These Emotions in Real Time. 1-What is Emotions Sensor Dataset: Emotions Sensor Data Set Contain Top 23 730 English Words Classified Statistically Using Naive Bayes Algorithm Into 7 Basic Emotion Disgust, Surprise ,Neutral ,Anger ,Sad ,Happy and Fear. 2-How We Build This Dataset: -First We Collected Thousands of Sentences , Blogs and Twitters . all about 1.185.540 Words -We Labeled Manually and Automatically this Sentences Into 7 Basic Emotion Disgust, Surprise ,Neutral ,Anger ,Sad ,Happy and Fear. -Now We Choose The Top of Most Used 23 730 English Words -Word by Word We Calculated The Probabilities of Existence of This Words in Disgust, Surprise ,Neutral ,Anger ,Sad ,Happy and Fear Sentences and Put Them in Simple CSV File -We Used The Naive Bayes Algorithm To Calculate This Probabilities Of Existence Of This Words 3-Where To Use This Dataset: Emotions Sensor DataSet Helps To Detect Emotions In Text or Voice Speech and You Can Easily Build a Sentiment Analysis Bot In few simple steps. Questions or Get the full Emotions Sensor Data Set Contain Top 23730 English Words ? To Get your copy of the full Emotions Sensor Data Set Or Contact me : codibitsgmail.com

8 features

wordstring1104 unique values
0 missing
disgustnumeric436 unique values
0 missing
surprisenumeric521 unique values
0 missing
neutralnumeric300 unique values
0 missing
angernumeric524 unique values
0 missing
sadnumeric516 unique values
0 missing
happynumeric525 unique values
0 missing
fearnumeric530 unique values
0 missing

19 properties

1104
Number of instances (rows) of the dataset.
8
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
7
Number of numeric attributes.
0
Number of nominal attributes.
0.01
Number of attributes divided by the number of instances.
87.5
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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