{ "data_id": "43756", "name": "Emotions--Sensor-Data-Set", "exact_name": "Emotions--Sensor-Data-Set", "version": 1, "version_label": "v1.0", "description": "Context\nEmotions Detection Is an Interesting Blend of Psychology and Technology.\n-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.\n-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.\n1-What is Emotions Sensor Dataset:\nEmotions 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.\n2-How We Build This Dataset:\n-First We Collected Thousands of Sentences , Blogs and Twitters .\nall about 1.185.540 Words \n-We Labeled Manually and Automatically this Sentences Into 7 Basic Emotion Disgust, Surprise ,Neutral ,Anger ,Sad ,Happy and Fear.\n-Now We Choose The Top of Most Used 23 730 English Words\n-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 \n-We Used The Naive Bayes Algorithm To Calculate This Probabilities Of Existence Of This Words\n3-Where To Use This Dataset:\nEmotions Sensor DataSet Helps To Detect Emotions In Text or Voice Speech and You Can Easily Build a Sentiment Analysis Bot In few simple steps.\nQuestions or Get the full Emotions Sensor Data Set Contain Top 23730 English Words ?\nTo Get your copy of the full Emotions Sensor Data Set Or Contact me : codibitsgmail.com", "format": "arff", "uploader": "Dustin Carrion", "uploader_id": 30123, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-24 07:52:01", "update_comment": null, "last_update": "2022-03-24 07:52:01", "licence": "Database: Open Database, Contents: Original Authors", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102581\/dataset", "default_target_attribute": null, "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Emotions--Sensor-Data-Set", "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 Consum " ], "weight": 5 }, "qualities": { "NumberOfInstances": 1104, "NumberOfFeatures": 8, "NumberOfClasses": null, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 7, "NumberOfSymbolicFeatures": 0, "Dimensionality": 0.007246376811594203, "PercentageOfNumericFeatures": 87.5, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "AutoCorrelation": null, "PercentageOfMissingValues": 0 }, "tags": [ { "uploader": "38960", "tag": "Demographics" }, { "uploader": "38960", "tag": "Health" } ], "features": [ { "name": "word", "index": "0", "type": "string", "distinct": "1104", "missing": "0" }, { "name": "disgust", "index": "1", "type": "numeric", "distinct": "436", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "surprise", "index": "2", "type": "numeric", "distinct": "521", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "neutral", "index": "3", "type": "numeric", "distinct": "300", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "anger", "index": "4", "type": "numeric", "distinct": "524", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "sad", "index": "5", "type": "numeric", "distinct": "516", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "happy", "index": "6", "type": "numeric", "distinct": "525", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" }, { "name": "fear", "index": "7", "type": "numeric", "distinct": "530", "missing": "0", "min": "0", "max": "0", "mean": "0", "stdev": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }