Essays about: "emotion detection"

Showing result 1 - 5 of 12 essays containing the words emotion detection.

1. 1. Design an emotionally positive experience via sentiment classification for social media recommendation systems : A case study in TikTok

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Yawen Deng; [2023]
   Keywords : recommendation system; social application; sentiment classification; emotions; UX; rekommendationssystem; social tillämpning; känslolägesklassificering; känslor; UX;

   Abstract : Recommendation system benefits social media by attracting users with the posts they prefer. The recommended posts, however, may not align with what users really need to browse, especially in terms of emotion. READ MORE

3. 2. AI Second that Emotion - Using Natural Language Processing to Study the Impact of Non-Stereotyped Video Advertising on Consumers’ Emotions & Online Consumer Engagement

   University essay from Göteborgs universitet/Graduate School

   Author : Amanda Hassel; Linnea Jonsson; Johan Strömfeldt; [2022-08-04]
   Keywords : Stereotype; Video Advertisement; Emotions; Online Consumer Engagement; Natural Language Processing NLP ; Artificial Intelligence AI ; Machine Learning; Bidirectional Encoder Representation from Transformers BERT ; Transformer Models;

   Abstract : This paper aims to provide a deeper understanding of the emotional and online engagement behavioral responses to non-stereotyped gender role depictions in video advertisements. The consumer response to two video ads that portray non-stereotyped gender roles by the well-known brands Gillette and Always was analyzed. READ MORE

4. 3. Emotion recognition with Deep Learning and its correlation with veracity

   University essay from Uppsala universitet/Institutionen för informationsteknologi

   Author : Emma Goodwin; [2022]
   Keywords : ;

   Abstract : Emotion recognition is an interesting and important field of study in many professional fieldssuch as medicine and law enforcement. This topic of study has many different challenges toexplore and we chose a few of these to expand upon. READ MORE

5. 4. Hotspot Detection for Automatic Podcast Trailer Generation

   University essay from Uppsala universitet/Institutionen för lingvistik och filologi

   Author : Winstead Xingran Zhu; [2021]
   Keywords : automatic podcast trailer generation; hotspot detection; speech emotion recognition; text emotion recognition; text arousal detection; pull-quote selection; music detection; laughter detection; affect analysis; affective computing; machine learning; neural network;

   Abstract : With podcasts being a fast growing audio-only form of media, an effective way of promoting different podcast shows becomes more and more vital to all the stakeholders concerned, including the podcast creators, the podcast streaming platforms, and the podcast listeners. This thesis investigates the relatively little studied topic of automatic podcast trailer generation, with the purpose of en- hancing the overall visibility and publicity of different podcast contents and gen- erating more user engagement in podcast listening. READ MORE

6. 5. Emotion Detection from Electroencephalography Data with Machine Learning : Classification of emotions elicited by auditory stimuli from music on self-collected data sets

   University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

   Author : Filip Söderqvist; [2021]
   Keywords : Electroencephalography; Deep learning; Machine learning; Likeability; Valence; Arousal; Emotion detection; Elektroencefalografi; Djupinlärning; Maskininlärning; Omtyckthet; Valens; Aktiveringsgrad; Känslodetektion;

   Abstract : The recent advances in deep learning have made it state-of-the-art for many different tasks, making its potential usefulness for analyzing electroencephalography (EEG) data appealing. This study aims at automatic feature extraction and classification of likeability, valence, and arousal elicited by auditory stimuli from music by training deep neural networks (DNNs) on  minimally pre-processed multivariate EEG time series. READ MORE