The last decade has been a time of great progress in the World Wide Web and this progress has manifested in multiple ways, including both the diffusion and expansion of Semantic Web technologies and the advancement of the aesthetics and usability of Web user interfaces. Online media outlets have often been popular Web destinations and so they are expected to be at the forefront of innovation, both in terms of the integration of new technologies and in terms of the evolution of their interfaces. In this study, various Web data extraction techniques were employed to collect current and archival data from news websites that are popular in Greece, in order to monitor and record their progress through time. This collected information, which took the form of a website’s source code and an impression of their homepage in different time instances of the last decade, has been used to identify trends concerning Semantic Web integration, DOM structure complexity, number of graphics, color usage, and more. The identified trends were analyzed and discussed with the purpose of gaining a better understanding of the ever-changing presence of the media industry on the Web. The study concluded that the introduction of Semantic Web technologies in online media outlets was rapid and extensive and that website structural and visual complexity presented a steady and significant positive trend, accompanied by increased adherence to color harmony.
On Instagram, we have all seen memes. Honestly, what would you do if you encountered a meme in a museum? The purpose of the study is to evaluate the nexus between posts uploaded by museum visitors and emotions, as well as the popularity of artworks and memes. We gathered N = 4.526 (N = 1.222 for memes and N = 3.304 for museum posts) entire posts using API. We selected the total number of likes, comments, frequency, nwords, and text emotions as indicators for several supervised machine learning tasks. Moreover, we used a ranking algorithm to measure meme and artwork popularity. Our experiments revealed the most prevalent emotions in both the memes dataset and museum posts dataset. The ranking task showed the most popular meme and museum post, respectively, that can influence the aesthetic experience and its popularity. This study provided further insight into the social media sphere that has had a significant effect on the aesthetic experience of museums and artwork’s popularity. As a final point, we anticipate that our outcomes will serve as a springboard for future studies in social media, art, and cultural analytics.
Social media is the most popular canvas to engage with art. In this study, we provide a different angle, on how an artistic installation on a world-renowned monument—such as Paris’ Arc de Triomphe—can emotionally affect viewers and potentially increase the popularity of the artwork. We collected N = 7078 Instagram and N = 3776 Twitter posts of the Arc de Triomphe as wrapped (installation) and unwrapped using APIs. As engagement indicators for several supervised machine learning experiments, we chose the total number of likes, comments, shares, text sentiment, and so on. Our findings revealed that people were captivated by the poetic installation. Based on the results, we discovered that the sentiments of triumph and surprise prevailed in datasets of the Arc de Triomphe as unwrapped. The same sentiments of triumph and surprise were most prevalent in datasets as wrapped, as well, but with higher scores. Furthermore, we have provided evidence of public art experience and engagement in the social media era. This research, we believe, will be useful in future studies of social media through the lens of public art and popularity. We hope that our findings will stimulate future research in the fields of art curatorship, cultural heritage management, marketing and communication, aesthetics, and culture analytics.
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