Machine Learning based Emotion classification in the COVID-19 Real World Worry Dataset

Hakan ÇAKAR; Abdulkadir SENGUR

Makale detayları

Machine Learning based Emotion classification in the COVID-19 Real World Worry Dataset

Yazarlar:

Hakan ÇAKAR | Abdulkadir SENGUR

Yayıncı:

Ali KARCI

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Computer Science 2021 Vol.6 Issue 1, pp.24-31

Belge Tipi:

Makale

Yayın Tarihi:

2/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000895887

Sıklık:

İki Yıllık

eISSN:

2548-1304

pISSN:

2548-1304

Özet:

 

COVID-19 pandemic has a dramatic impact on economies and communities all around the world. With social distancing in place and various measures of lockdowns, it becomes significant to understand emotional responses on a great scale. In this paper, a study is presented that determines human emotions during COVID-19 using various machine learning (ML) approaches. To this end, various techniques such as Decision Trees (DT), Support Vector Machines (SVM), k-nearest neighbor (k-NN), Neural Networks (NN) and Naïve Bayes (NB) methods are used in determination of the human emotions. The mentioned techniques are used on a dataset namely Real World Worry dataset (RWWD) that was collected during COVID-19. The dataset, which covers eight emotions on a 9-point scale, grading their anxiety levels about the COVID-19 situation, was collected by using 2500 participants. The performance evaluation of the ML techniques on emotion prediction is carried out by using the accuracy score. Five-fold cross validation technique is also adopted in experiments. The experiment works show that the ML approaches are promising in determining the emotion in COVID-19 RWWD. More specifically, the NN method produced the highest average accuracy scores for both emotion and gender classification where a 75.7% and 72.1% average scores were obtained.

Makale detayları

Machine Learning based Emotion classification in the COVID-19 Real World Worry Dataset

Yazarlar: Hakan ÇAKAR | Abdulkadir SENGUR

Yayıncı: Ali KARCI

Ana Başlıklar: Veri işleme & bilgisayar bilimi

Dergi: Computer Science 2021 Vol.6 Issue 1, pp.24-31

Belge Tipi: Makale

Yayın Tarihi: 2/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000895887

Sıklık: İki Yıllık

eISSN: 2548-1304

pISSN: 2548-1304

Sayı

Yazarlar:

Hakan ÇAKAR | Abdulkadir SENGUR

Yayıncı:

Ali KARCI

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Computer Science 2021 Vol.6 Issue 1, pp.24-31

Belge Tipi:

Makale

Yayın Tarihi:

2/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000895887

Sıklık:

İki Yıllık

eISSN:

2548-1304

pISSN:

2548-1304