A significant addition to the field of Human-Computer Interaction is provided by
Baughan et al.'s (2022) essay "I Don't Even Remember What I Read": How Design
Influences Dissociation on social media. (HCI). The writers delve into the psychology of
dissociation, or "checking out" of one's mind when using social media. In their view,
dissociation is a widespread problem that can severely affect psychological health. This
article examines how specific social media interface design aspects promote disconnection
and presents suggestions for improving these interfaces. After introducing the topic of
dissociation and social media use, the authors thoroughly review the current research in this
area. They highlight that social media has become an indispensable tool for many, but it is
also linked to adverse effects, including heightened sensitivity to stress and other mental
health issues. They propose separation as a defense strategy against the barrage of
information and sensations that may be found on social media. (Get help with your
Coursework from Cheap Coursework Writing Services).
The writers of this article go into the link between design and dissociation by
detailing their research. Surveys, in-depth interviews, and a card-sorting exercise were all a
part of this study's multi-pronged methodology. The authors solicited help from users of the
popular crowdsourcing platform Mechanical Turk on Amazon's website. Several aspects of
the study's design were reviewed by the authors and shown to contribute to dissociation. The
scientists discovered that dissociation was greatly aided by the prevalence of auto-playing
movies, endless scrolling, and push alerts. They claim that these design aspects produce an
endless stream of material that users feel obliged to consume, even if they lack the cognitive
resources. The authors suggest a number of changes to the design, including letting users mute auto-playing movies and reducing the amount of information that may be shown at once.
This article is an excellent resource for learning more about how design and
dissociation shape user experiences across various social networking sites. The research done
by the writers is thorough, and it forms a firm basis for the design suggestions they make.
Practical and easily applied, the authors' suggestions might help social media sites lessen
dissociation's detrimental effects. There is also a significant addition to this paper's more
considerable HCI literature. It emphasizes the need to think about the user's mental and
emotional state while creating interfaces. It highlights the significance of designers being
aware of the potential unfavorable results of design decisions and placing a premium on user
satisfaction. The article's weaknesses include its reliance on Amazon's Mechanical Turk
platform for participant recruitment. Concerns have been raised regarding the platform's
participant pool needing more representatives, despite its widespread usage in HCI research.
In light of this restriction, the authors suggest diversifying participant recruitment strategies
for future studies. The article by Baughan et al. (2022) makes an essential addition to the
field of HCI. It offers valuable insights into the connection between design and dissociation
on social media platforms and suggests design ideas to address the problem. The essay also
stresses the need to prioritize user happiness by considering their mental and emotional state during the design process. While the essay does admit to certain possible pitfalls, it is, on balance, a solid investigation that sheds light on a pressing topic in the modern digital world. This paper is required reading for designers, scholars, and anybody concerned with how technology affects our psyches.
Chung, J. J. Y., Kim, W., Yoo, K. M., Lee, H., Adar, E., & Chang, M. (2022).
TaleBrush: Sketching Stories with Generative Pretrained Language Models. CHI
Conference on Human Factors in Computing Systems.
https://doi.org/10.1145/3491102.3501819
In Human-Computer Interaction, Chung et al.'s (2022) article "TaleBrush: Sketching
Stories with Generative Pretrained Language Models" represents a significant advancement.
(HCI). TaleBrush is a revolutionary interactive storytelling system proposed by the authors
that use generative pre-trained language models (GPT) to facilitate tale creation. This paper
surveys the relevant literature, introduces the TaleBrush system, and assesses its effectiveness
via a user study. In the first part of their paper, the authors survey prior research in interactive
storytelling. They stress the need for user-generated material and make interactive stories
difficult. The authors next present the idea of GPT, which has had extensive application in
NLP projects. They state that GPT may help users by producing text based on user input and
making suggestions while writing their stories. Next, TaleBrush, an innovative hybrid of
drawing and GPT, is introduced. Users of TaleBrush can draw a scene, and subsequently, a
story will be generated by a GPT model. The user can change the story by picking from a list
of suggested sentences or manually entering their own words. After the user edits the tale, the
system creates a new drawing based on the revised plot. The authors surveyed 24 users to see
how satisfied they were with TaleBrush. Each participant in the research wrote two stories,
one with the assistance of TaleBrush and one in the control condition where they were
instructed to write a narrative without any external aid. The quality of the stories, the time it
took to accomplish the assignment, and the user's subjective experience were only some of
the data collected by the writers.
