more of the same but different CHAPTERS 0:00 Memes 2:59 Sequels, Remakes and Adaptations 4:41 Genres 5:40 Superheroes 8:50 What We Want 10:00 The Point 11:30 Into the Spider-Verse 14:24 Close https://www.everythingisaremix.info/watch-the-series/
For starters, every interaction a person has with a digital product follows the same pattern: Information — User filters the information Significance — User looks for its meaning Time — User takes an action within a time frame Memory — User stores fragments of the interaction in their memory For each of these stages of interaction, I’ve compiled a list of the most relevant design principles and cognitive biases that will help you to build habit-forming products.
Results In the 34 day period after the three events with the strongest public attention (the song’s release, the MTV Video Music Awards 2017, and Grammy Awards 2018), Lifeline received an excess of 9915 calls (95% confidence interval 6594 to 13 236), an increase of 6.9% (95% confidence interval 4.6% to 9.2%, P
Welcome to the Entertainment Industry’s Guide to Mental Health Storytelling Developed by a groundbreaking coalition of mental health experts and entertainment industry leaders.
Low self esteem is the best predictor
Protobot generates random product and service ideas.
You may be wondering: If users want personalization, then what’s the problem? The problem is that personalization is a bit like walking a tightrope. A very thin line separates the “good” kind of personalization from the creepy kind. “I like it because it’s so similar to me” can easily become “I don’t like it because it’s eerily similar to me.” “This is relevant to me and saves me time and effort” can easily become “The algorithm is stereotyping me and that’s not cool.” This switch from good to bad is where user psychology comes in. Understanding the real reason why personalization works can help us understand why it does not work sometimes.
That’s why we’ve developed an evidence-based approach to identifying and prioritising the most suitable behaviour(s) to address a problem: The Impact-Likelihood Matrix (ILM), developed by our very own Sarah Kneebone. By undertaking a rigorous investigation of the literature and audience research, our technique ensures that the behaviour(s) you choose to target for your intervention or policy will have the highest likelihood of driving the change you are seeking.
Prioritizing work into a roadmap can be daunting for UX practitioners. Prioritization methods base these important decisions on objective, relevant criteria instead of subjective opinions. This article outlines 5 methods for prioritizing work into a UX roadmap: Impact–effort matrix Feasibility, desirability, and viability scorecard RICE method MoSCoW analysis Kano model These prioritization methods can be used to prioritize a variety of “items,” ranging from research questions, user segments, and features to ideas, and tasks.
This toolkit outlines broad concepts of branding, post design, and post management. It also provides details, suggestions, and tips on how to create an account, gain a following, increase engagement, and more on both Facebook and Instagram. . Lastly, it details the process of using paid Facebook and Instagram advertisements for research purposes (i.e., recruiting participants).
From 10 to 25 is a collaborative storytelling game about the period of life we call adolescence. Players take on the role of a young person making their way through adolescence. Players combine the experiences life has dealt them with relationships and resources available in their community to tell a story about growing up. The game builds understanding of what adolescence is and what young people need to thrive.
Results show 9–17 interviews or 4–8 focus group discussions reached saturation.
The Meta-Analysis Learning Information Center (MALIC) believes in equitably providing cutting-edge and up-to-date techniques in meta-analysis to researchers in the social sciences, particularly those in education and STEM education.
Controlling for expected value, we found that a policy combining a high probability of inspection with a low severity of fines (HILS) was more effective than an economically equivalent policy that combined a low probability of inspection with a high severity of fines (LIHS). The advantage of prioritizing inspection frequency over punishment severity (HILS over LIHS) was greater for participants who, in the absence of enforcement, started out with a higher violation rate. Consistent with studies of decisions from experience, frequent enforcement with small fines was more effective than rare severe fines even when we announced the severity of the fine in advance to boost deterrence.
If you write briefs as part of your job, read & bookmark this. So much that’s NB & useful, from truly interrogating the objective, to making sure the different sections line up, to writing your proposition as a headline, to the brief being a dynamic doc open to improvement.
How many interviews are enough depends on when you reach saturation, which, in turn, depends on your research goals and the people you’re studying. To avoid doing more interviews than you need, start small and analyze as you go, so you can stop once you’re no longer learning anything new.
awful example of landing page!
Narrative capture is when an industry, company, or group changes the common narrative for their benefit, even if that just means changing the status quo. What are our baseline expectations? What is acceptable behavior? What is the way we measure fairness? What should we complain about? As expected, narrative capture is different. Here are some of its forms.
“...Public health’s attempts at being apolitical push it further toward irrelevance. In truth, public health is inescapably political, not least because it has to make decisions in the face of rapidly evolving and contested evidence.“
Then our hero enters, and decides to coordinate and plan a persuasion campaign to get the rule changed. Here’s how I think this went down. He in advance arranges for various sources to give him a signal boost when the time comes, in various ways. He designs the message for a format that will have maximum reach and be maximally persuasive. This takes the form of an easy to tell physical story, that he pretends to have only discovered now. Since all actual public discourse now takes place on Twitter, it takes the form of a Twitter thread, which I will reproduce here in full.
For HCI survey research broadly, we recommend using a question similar to the first question in [2]’s measure (as quoted in [3]) – “Are you…?” with three response options: “man,” “woman,” “something else: specify [text box]” – and allowing respondents to choose multiple options. This question will not identify all trans participants [3], but is inclusive to non-binary and trans people and will identify gender at a level necessary for most HCI research. To reduce trolling, we recommend providing the fill-in-theblank text box as a second step only for those respondents who choose the “something else” option.
I love it that one of my students suggested we change the default “Other (please specify“) option to “Not Listed (please specify)“ in a demographic survey. Explicitly *not* “othering“ participants while still asking for the info we want. Any implied failure is on us, not them.
There are surely many ways in which our beliefs can be quite nuanced. We examined the different ‘styles’ of belief we come up against in a variety of the work we do and observed a number of ways these styles appear: Suspension of disbelief: We know not to look too closely at something – we think that overall it is a good thing (e.g. recycling) but aware of possible discrepancies (e.g. being poorly disposed of) that may or may not lead us to question our positive beliefs. We are aware of the possible conflicts but this does not make our belief in the value of recycling any less valid. There are a great many beliefs that we have that could be challenged yet they serve us sufficiently well that we do not need to interrogate them too closely (political representation, eating meat) Inconsistent beliefs: Linked to this, we may hold two conflicting beliefs at the same time. We may know that wild fires are a natural phenomenon that predates climate change; but also that the fires we see in many areas today are of a much greater intensity and frequency. Exactly which is responsible cannot really be picked out, we can only really see the patterns emerging at a more macro-level, so it is not unreasonably to either hold both as true for even consider that the fire you have experience is a normal wild fire. Off-loading beliefs to others: Much of the time our beliefs about how things work is not something that we each individually work out, but we rely on a community of knowledge to work on our behalf. How many of us can be sure that our beliefs are correct about how vaccines work or indeed even how a zipper work. If we are questioned, then we recognise that our belief about how something works is tenuous but we have a good enough sense of it that allows us to function. Unformed beliefs: Sometimes we have not quite worked out what our beliefs are about something, which means that we may well move about in those beliefs or in the strength to which we hold onto them. The vaccination example outlined earlier is a good case in point. Not sure fully believe it but ‘there is something in it’ beliefs: Recent work we have been doing on Conspiracy Theories suggests that people may consider something is believable (e.g. Princess Diana’s death in a car crash was not accidental) but at the same time, in a different question then say they ‘do not fully believe it but there is something in it’. So what might seem like a belief is actually something much more akin to a questioning stance.
“We’re basically creating an MCU-style universe of characters on TikTok,” says Benjamin. “Some succeed, some fail — it’s the TV pilot season model where we only invest in those that get traction and audiences love.”
CONCLUSIONS Debunking strategies that repeat vaccination myths do not appear to be inferior to strategies that do not repeat myths.
