China
Africa
Explore chapters and articles related to this topic
The Interactive Interim
Published in Ed Shane, Michael C. Keith, Selling Electronic Media, 1999
Because attention is a limited resource, Goldhaber’s theory is that ours is—or will be—an “attention economy.” Attention is scarce, Goldhaber wrote in Wired, “and the total amount per capita is strictly limited. … The size of the attention pie can grow as more and more people join the world audience, but the size of the average slice can’t.”
Ethical, political and epistemic implications of machine learning (mis)information classification: insights from an interdisciplinary collaboration between social and data scientists
Published in Journal of Responsible Innovation, 2023
Andrés Domínguez Hernández, Richard Owen, Dan Saattrup Nielsen, Ryan McConville
A perhaps more fundamental issue with the use of algorithmic misinformation detection is that it emphasises the role of individual consumers and producers of misinformation at the expense of downplaying the interests and responsibilities of major technology companies. The business model of social media platforms is based on maximising the time users spend on their platforms in order to generate advertising revenue. This is achieved through opaque algorithms of personalisation and recommendation based on people’s behaviour, demographics and preferences (Zuboff 2019). The attention economy rewards the circulation of (and engagement with) content regardless of its quality; and in fact, misinformation has been found to consistently receive widespread attention and engagement in social media platforms (Edelson et al. 2021). One could argue that the commercial incentive of platforms to maximise engagement is thus at odds with the goal of meaningfully tackling the spread of misinformation and any type of content that could lead to downstream harms.
Visual Attention Quality Research for Social Media Applications: A Case Study on Photo Sharing Applications
Published in International Journal of Human–Computer Interaction, 2023
Xian Yang, Bin Yang, Chaolan Tang, Xiaohong Mo, Bin Hu
The study of visual attention is one of the biggest challenges in the user experience design of SMA products as SMA products of different types or positioning may have different focuses on visual attention. For example A comparison between Instagram, an SMA based on image sharing, and Twitter, another SMA based on text sharing, reveals that the SMA based on image sharing can lead to a lower level of loneliness through social interaction and higher concentration of attention (Pittman & Reich, 2016). According to studies on the differences in the degree of user interaction for different types of images posted on Instagram, pictures with human faces tend to get more likes and saves (Bakhshi et al., 2014). This may be because Instagram users are mainly motivated to “know others” and “play cool” (Sheldon & Bryant, 2016). In addition, compared to TikTok and other video sharing-based SMA products that basically adopt a linear layout, photo-sharing applications resort to a variety of forms including matrix layout, masonry layout, and linear layout. Although the three layouts are commonly used, there is currently no strict definition of them. Therefore, in this paper, the matrix layout refers to Instagram-like Layout, the masonry layout to Pinterest-like Layout, and the linear layout to Flickr-like Layout. From the perspective of user tasks, no matter what kind of layouts SMA products use, they all have typical task stages such as search, execution, transfer, and termination, and different aspects of visual attention are highlighted at different stages (Dalmaso et al., 2020; Mo et al., 2023). Studying the aspects of visual attention of users in different stages so as to attract and maintain their attention on the product, can not only increase the user efficiency in information ingestion, save their time cost, but also bring more traffic to the enterprises and create more revenue, and this is what the now popular attention economy is about (Nelson-Field, 2020).