Open AccessCross-Media Sentiment Analysis on German Blogs
Author(s) -
Ni. Zahn,
Greice Pinho Dal Molin,
Soraia Raupp Musse
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/semish.2021.15813
Subject(s) - feeling , german , sentiment analysis , social media , computer science , the internet , perception , automation , domain (mathematical analysis) , artificial intelligence , psychology , natural language processing , world wide web , social psychology , linguistics , engineering , mechanical engineering , philosophy , neuroscience , mathematical analysis , mathematics
Social interactions have changed in recent years. People post their thoughts, opinions and feelings on social media platforms more often. Due to the increase in the amount of data on the internet, it is impracticable to carry out the sentiment analysis manually, requiring automation of the process. In this work, we present the corpus Cross-Media German Blog (CGB) which consists of German blogs with feelings in the domain of images, texts and posts (Ground Truth), classified according to human perceptions. We apply existing Machine Learning technologies and lexicons to the corpus to detect the feelings (negative, neutral or positive) of the images and texts and compare the results with the GT. We examined contradictory posts, when the image and text classified by humans in the same post had diverging feelings. The comparison of this article with the analysis of sentiment among the media of Brazilian blogs finds its justification for performance results in cultural differences, since, throughout this work, Brazil is classified as indulgent and Germany as a restrained country.