Pregled bibliografske jedinice broj: 1134125
Sentiment Analysis of the Infographics on Social Media
Sentiment Analysis of the Infographics on Social Media // Proceedings of FEB Zagreb International Odyssey Conference on Economics and Business / Načinović Braje, Ivana ; Jaković, Božidar ; Ferjanić Hodak, Danijela (ur.).
Zagreb: Ekonomski fakultet Sveučilišta u Zagrebu, 2021. str. 1073-1082 doi:10.22598/odyssey/2021.3 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Sentiment Analysis of the Infographics on Social
Media
Autori
Bratić, Diana ; Palić, Mirko ; Miljković, Petar
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of FEB Zagreb International Odyssey Conference on Economics and Business
/ Načinović Braje, Ivana ; Jaković, Božidar ; Ferjanić Hodak, Danijela - Zagreb : Ekonomski fakultet Sveučilišta u Zagrebu, 2021, 1073-1082
Skup
12th International Odyssey Conference on Economics and Business
Mjesto i datum
Zagreb, Hrvatska, 09.06.2021. - 12.06.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
sentiment analysis ; infographics ; social media
Sažetak
Today, the Internet is the main source of information for both users and businesses. Communication and exchange of information are two- way, but results are often obtained unstructured, multimodal, informal, high- dimensional, and noisy. This is especially pronounced with data collected from social media which are an indispensable marketing tool. A large number of active users allows you to quickly spread the sent message, while also providing almost instant feedback. However, not all forms of sent messages are noticed and spread equally. Therefore, in this paper, a sentimental analysis of the users’ reactions was made. Multimodal data were used to collect users’ reactions: text publication, image publication, and infographics on the topic of ecology. All three types of publications are posted on three social media, Facebook, Twitter, and LinkedIn. Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine, and Neural Network Algorithms were used to automatically assess sentiment as positive, negative, or neutral. The results thus given show the best overall performance for Decision Tree classifier on all types of users’ reactions. Then follows Random Forest and finally Naïve Bayes classifier. Also, the obtained results show data linearity from which it can be concluded that on whatever social media it is published, infographics certainly has a leading position when it comes to spotting and getting users’ reactions, especially positive ones.
Izvorni jezik
Engleski
Znanstvena područja
Grafička tehnologija, Ekonomija, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Ekonomski fakultet, Zagreb,
Grafički fakultet, Zagreb