Reconceptualizing the Work of a Content Provider for an Online Audience: A Case Study for How Pedagogical Strategies Can Provide Models of Engagement for Producers of Entertainment

With the interconnectivity of the Internet, and the availability of affordable media compositional tools, the proliferation of online media continues to grow exponentially. However, each day is still comprised of a fixed 24 hours, with far fewer hours spent in active media consumption. Considering the global potential for content to be found (Moreville), discovered (Cormier) or spread (Jenkins), content providers are looking for ways to attract, cultivate and hopefully expand their audiences amid all this digital clutter. In the field of entertainment, this challenge is complicated when small content providers are not aligned with an online, curated network such as Netflix or Hulu. Online education has developed practices designed to communicate expectations/objectives and increase engagement. Although the outcomes/objectives between the entertainment industry and those of online education are quite different, it is possible that both industries could find commonality and share mutually beneficial approaches. Conceptualizing the audience as students might offer content providers a quicker path to assessing what their “work” is online and following a cyclical process of evaluation, as in education, offers a logical and almost narrative approach to data collection and assessment. Using both qualitative and quantitative methods, this project examines several phases of audience activities surrounding three versions of an online animated comedy series on YouTube and a related official web page: (a) the original version created before an eLearning framework was employed; (b) a second version six months later, where some practices were implemented; and (c) a third version six months after the second phase, which employed more changes. Examination phases before and after the series had ended provide additional opportunities for study. The data suggest that modifying entertainment content with an educational framework helped increase audience engagement in that more viewers consumed content and participated in related creative acts. Viewership jumped after the original episode formats and webpage had been modified. However, after the main phases ended, other Internet activities also impacted viewership. This cyclical, educational framework could be useful to other small entertainment providers who struggle with social media and seek to enhance audience engagement in a cluttered social space

PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models

Large Language Models (LLMs) have gained widespread popularity due to their ability to perform ad-hoc Natural Language Processing (NLP) tasks with a simple natural language prompt. Part of the appeal for LLMs is their approachability to the general public, including individuals with no prior technical experience in NLP techniques. However, natural language prompts can vary significantly in terms of their linguistic structure, context, and other semantics. Modifying one or more of these aspects can result in significant differences in task performance. Non-expert users may find it challenging to identify the changes needed to improve a prompt, especially when they lack domain-specific knowledge and lack appropriate feedback. To address this challenge, we present PromptAid, a visual analytics system designed to interactively create, refine, and test prompts through exploration, perturbation, testing, and iteration. PromptAid uses multiple, coordinated visualizations which allow users to improve prompts by using the three strategies: keyword perturbations, paraphrasing perturbations, and obtaining the best set of in-context few-shot examples. PromptAid was designed through an iterative prototyping process involving NLP experts and was evaluated through quantitative and qualitative assessments for LLMs. Our findings indicate that PromptAid helps users to iterate over prompt template alterations with less cognitive overhead, generate diverse prompts with help of recommendations, and analyze the performance of the generated prompts while surpassing existing state-of-the-art prompting interfaces in performance

"how over is it?" Understanding the Incel Community on YouTube

YouTube is by far the largest host of user-generated video content worldwide. Alas, the platform has also come under fire for hosting inappropriate, toxic, and hateful content. One community that has often been linked to sharing and publishing hateful and misogynistic content are the Involuntary Celibates (Incels), a loosely defined movement ostensibly focusing on men's issues. In this paper, we set out to analyze the Incel community on YouTube by focusing on this community's evolution over the last decade and understanding whether YouTube's recommendation algorithm steers users towards Incel-related videos. We collect videos shared on Incel communities within Reddit and perform a data-driven characterization of the content posted on YouTube. Among other things, we find that the Incel community on YouTube is getting traction and that, during the last decade, the number of Incel-related videos and comments rose substantially. We also find that users have a 6.3% chance of being suggested an Incel-related video by YouTube's recommendation algorithm within five hops when starting from a non Incel-related video. Overall, our findings paint an alarming picture of online radicalization: not only Incel activity is increasing over time, but platforms may also play an active role in steering users towards such extreme content

Investigating users’ mental models of traditional and digital libraries

There is much HCI-related literature on mental models and on the usability of digital libraries, however there is no previously published literature on users’ mental models of either traditional or digital libraries. This is surprising, since many digital libraries are difficult to use and it is not immediately clear why. Our study begins to fill this void by examining users’ mental models of traditional and digital libraries through a series of Contextual Inquiry interviews that mix traditional think-aloud observations, which usually demand minimal researcher intervention, and semi-structured interviews, which usually demand significant intervention. The study finds that participants’ mental models of traditional and digital libraries extend beyond surface similarities and differences, such as the hierarchical organisation of items in both types of library and the availability of documents in paper and electronic mediums. These models contain deeper similarities and differences based on the information-seeking goals that can be fulfilled by each type of library, issues concerning the contents and relevance of individual documents and entire libraries, and ‘how searching works’ and how to ‘troubleshoot’ in both types of library. Although the use of concrete analogies to influence users’ understanding or usage of digital libraries was not widespread, participants used their knowledge of Internet search engines to infer how searching might work in digital libraries. Additionally, most participants assumed that even if different at the interface level or at the level of the underlying technology employed, the search components of digital libraries, Internet search engines and other digital entities work in a similar way to bring back search results. The study also finds that a large component of users’ mental models of digital libraries is the notion of access restrictions. The insights gained from the observations relating to the above recurring themes in users’ mental models are discussed with a view of helping to improve digital library usability by reducing access restrictions and notifying users of any such restrictions upfront, by providing dynamic and context-dependent help to users, by carefully introducing analogies into the digital library interface (if and where appropriate) and by making multiple digital libraries searchable under a single front-end to enable them to be accessed, browsed and searched in the same way

Seeking Relevance in a Social Media Age: A Guide for the FRAXA Research Foundation

The purpose of this project was to provide the FRAXA Research Foundation with recommendations for improving social media presence on Facebook, Twitter, and YouTube. By performing a SWOT analysis, creating experiments, and analyzing data from social media accounts, we demonstrated the importance of posting frequently, tailoring content to specific audiences, and cross-posting to maintain a strong social media presence. These strategies will help FRAXA increase outreach and obtain a higher likelihood of donors and volunteers dedicated to advancing FRAXAÂ’s mission

Investigating users’ mental models of traditional and digital libraries

There is much HCI-related literature on mental models and on the usability of digital libraries, however there is no previously published literature on users’ mental models of either traditional or digital libraries. This is surprising, since many digital libraries are difficult to use and it is not immediately clear why. Our study begins to fill this void by examining users’ mental models of traditional and digital libraries through a series of Contextual Inquiry interviews that mix traditional think-aloud observations, which usually demand minimal researcher intervention, and semi-structured interviews, which usually demand significant intervention. The study finds that participants’ mental models of traditional and digital libraries extend beyond surface similarities and differences, such as the hierarchical organisation of items in both types of library and the availability of documents in paper and electronic mediums. These models contain deeper similarities and differences based on the information-seeking goals that can be fulfilled by each type of library, issues concerning the contents and relevance of individual documents and entire libraries, and ‘how searching works’ and how to ‘troubleshoot’ in both types of library. Although the use of concrete analogies to influence users’ understanding or usage of digital libraries was not widespread, participants used their knowledge of Internet search engines to infer how searching might work in digital libraries. Additionally, most participants assumed that even if different at the interface level or at the level of the underlying technology employed, the search components of digital libraries, Internet search engines and other digital entities work in a similar way to bring back search results. The study also finds that a large component of users’ mental models of digital libraries is the notion of access restrictions. The insights gained from the observations relating to the above recurring themes in users’ mental models are discussed with a view of helping to improve digital library usability by reducing access restrictions and notifying users of any such restrictions upfront, by providing dynamic and context-dependent help to users, by carefully introducing analogies into the digital library interface (if and where appropriate) and by making multiple digital libraries searchable under a single front-end to enable them to be accessed, browsed and searched in the same way