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- 저자 : Mohammad Aman Ullah (검색결과 2 건)
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An algorithm and method for sentiment analysis using the text and emoticon
Mohammad Aman Ullah,Syeda Maliha Marium,Shamim Ara Begum,Nibadita Saha Dipa 한국통신학회 2020 ICT Express Vol.6 No.4
People nowadays use emoticons in their text increasingly in order to express their feelings or recapitulate their words. Earlier machine learning techniques only involve the classification of text, emoticons or images solely where emoticons with text have always been neglected, thus ignored lots of emotions. This research proposed an algorithm and method for sentiment analysis using both text and emoticon. In this work, both modes of data were analyzed in combined and separately with both machine learning and deep learning algorithms for finding sentiments from twitter based airline data using several features such as TF–IDF, Bag of words, N-gram, and emoticon lexicons. This research demonstrates that whenever emoticons are used, their associated sentiment dominates the sentiment conveyed by textual data analysis. Also, deep learning algorithms are found to be better than machine learning algorithms.
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Urmy Nushrat Jahan,Hossain Md. Mokbul,Shamim Abu Ahmed,Khan Md. Showkat Ali,Hanif Abu Abdullah Mohammad,Hasan Mehedi,Akter Fahmida,Mitra Dipak Kumar,Hossaine Moyazzam,Ullah Mohammad Aman,Sarker Samir 질병관리본부 2020 Osong Public Health and Research Persptectives Vol.11 No.6
Objectives To assess the prevalence of noncommunicable disease (NCD) risk factors and the factors associated with the coexistence of multiple risk factors (≥ 2 risk factors) among adolescent boys and girls in Bangladesh. Methods Data on selected NCD risk factors collected from face to face interviews of 4,907 boys and 4,865 girls in the national Nutrition Surveillance round 2018–2019, was used. Descriptive analysis and multivariable logistic regression were performed. Results The prevalence of insufficient fruit and vegetable intake, inadequate physical activity, tobacco use, and being overweight/obese was 90.72%, 29.03%, 4.57%, and 6.04%, respectively among boys; and 94.32%, 50.33%, 0.43%, and 8.03%, respectively among girls. Multiple risk factors were present among 34.87% of boys and 51.74% of girls. Younger age (p < 0.001), non-slum urban (p < 0.001) and slum residence (p < 0.001), higher paternal education (p = 0.001), and depression (p < 0.001) were associated with the coexistence of multiple risk factors in both boys and girls. Additionally, higher maternal education (p < 0.001) and richest wealth quintile (p = 0.023) were associated with the coexistence of multiple risk factors in girls. Conclusion The government should integrate specific services into the existing health and non-health programs which are aimed at reducing the burden of NCD risk factors.
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