March 2022 | Case study.
Alirtify
Be
informed.
Stay alert.
Alirtify is an intelligence-gathering platform that uses data from news events such as sentiments (positive, neutral, negative), location, and keywords to glean real-time insights.
USP: to provide society with a unique opportunity to push local news to the forefront and change the narrative on what truly matters to local communities.
Team
Amanpreet Kaur, Agnes Joseph, Krithika Balasubramanian, Meghan Lendhe, Sushanth Hegde, Sparsh Paliwal
My Role
Researcher,
Responsible for primary communication between client and team.
Client
Kwabena Okrah, CEO, Alirtify.
Duration
2.5 months
Overview
Alirtify was in the process of curating a new version of their application. As a part of this project, we were assigned with the task of conducting contextual inquiry into how people are currently consuming news and suggest upgrades that can help Alirtify become the go-to news application for news validation.
Problem Statement
The pandemic has seen an uptake in the perpetuation of misinformation among news sources, with consumers becoming distrustful of what they see on the media. This case study is aimed at understanding what resources might help users differentiate between fake and real news, and allow them to form their own opinions about global and local events.
Discover
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Stakeholder interview.
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Preliminary research.
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User interviews.
Define
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Affinity mapping.
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Wall walk.
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Identity model.
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Decision model.
Design
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Existing app and its issues
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Hot ideas
Evaluate
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Stakeholder feedback
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Reflection
Discover
Preliminary Research
After an initial discussion with the CEO of Alirtify, Mr Kwabena Okrah, extensive research was conducted into changes in the way users consume news in the post-pandemic era. We derived at the following set of questions that were to be the focus of the study:
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How might we help people distinguish fake news from real news?
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How are people currently validating news?
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How are user's consuming their news (products, apps, internet)?
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What visual cues can we provide to the users to help them distinguish fake news?
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Does the visual aspect of the way a news snippet is presented influence people's opinion of it being real or fake?
User Interviews
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For the purpose of this study we targeted users across age groups and backgrounds to explore differences in patterns regarding news consumption and validation.
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Our questions were based on our research statement to find out what journey users take and what factors influence those steps, when it comes to news consumption.
Age Range
Occupation
51- 60
51- 60
21- 30
21 - 30
21 - 30
21 - 30
21 - 30
Government Employee
Government Employee
Grad Student
Grad Student
Grad Student
Grad Student
Software Engineer
Collecting Data Points
Initially we conducted interviews with 6 participants. During interpretation we found patterns on how the users were consuming news:
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The younger participants tend to consume news through apps and social media, using platforms like Google and Twitter to validate.
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Older participants tend to consume news through print media, radio, television and friends/family.
On discussion we realized we needed an additional data point of a user from a younger age group who was not a student, to understand the influence of age vs occupation on news consumption patterns.
For this purpose we conducted additional user interview with another participant from the age group 21-30 who was a Software Engineer, working professionally for 3+ years.
Affinity Mapping & Wall Walk.
Affinity mapping was done based on the user data to get a bigger picture of the problem. In creating the Affinity Diagram, the research team identified two overarching themes, which are represented by pink labels. These green labels reflect the user story at the highest level and can be used to navigate the rest of the diagram.
The two themes synthesized in the Affinity Diagram gave an overview of the different ways the participants interact with news in their lives and also how they differentiate between real and fake news.
Define
Users are interested in consuming trustworthy news and have different ways of validating it:
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Users have different preferences for the methods through which they get news:
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Identity Model
We used the identity model to articulate user personalities, beliefs and their behavior with respect to news consumption. Through our interviews we were able to identify certain user identities, which were not clearly showcased in the affinity diagram.
Each identity has associated “Give Mes,” which provides concrete suggestions to improve the user experience for that particular identity cluster. For example, the Googler from “I do” is an individual who likes to clarify their doubts using Google when something about the news articles they come across feels wrong to him. The “Give Mes” for the Googler suggests providing them with an interface which displays top related articles from google to an article they are reading
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Decision Point Model
Decision Point Models reveal what influences important decisions. We took up the Decision Point Model to figure out the factors that influence the users' critical decision of engaging with the news or not. These findings can be used to conceptualize features and validate design decisions of the product to ensure that the product’s objective of sharing trustworthy news is met.
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Takeaways
From the decision point model we identified 3 main factors that influence how people consume and perceive news.
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Sources - People trust news when it comes to sources they trust. So it is important to highlight the source of the article and tailor the newsfeed to the preference of the user.
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Characteristics - People take into consideration the visual appearance and tone of voice of the news article when determining its validity. Biased and overly emotional news comes off as fake. People also trust an article linked to scientific studies.
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Preferences - Making news more easy to access would encourage more users to engage with the product
Design
Design Analysis
Comparing the current interface with our findings.
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Source of the news article is not prominent: The current application did not show the source of the news prominently. However, according to our findings, we realized that the source of the article was an important factor in influencing whether a user might engage with an article.
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No indication of engagement from close social circle: For each news article displayed in the feed of the app, only the interaction details (views, likes, reactions) of the world was displayed. There was no indication of how many of the user’s close circle of friends/family interacted with the article. However, based on the research, validation from a user’s social circle is an important factor in determining if the user will engage with the article.
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Users preference to self-validate their news: Our research uncovered that a user’s belief system influences their perception of news. For this purpose, there must be a presence of elements that are unbiased for example data backed by official sources, or a presence of articles from various sources which differ in opinion so users can make up their own minds about the validity of what they are reading. This feature is missing from the current app, which instead has opinions from the general public.
Redesign
With the issues identified, we moved on to designing a few solutions which might help users better consume news in Alirtify.
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Easy access to News: Better notifications of subscribed or interesting topics can be pushed to the user's device. The interesting topics can be related to people/contacts they follow or pertain to a particular region, thereby keeping the user’s always updated.
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Generating unbiased headlines for each article: We discovered that clickbait headlines always turn readers away during our investigation. As a result, if Alirtify uses AI to convert the original headlines into unbiased ones, it will not only assist users in getting a sense of what they are getting into, but it will also help to reduce the spread of misinformation by preventing readers from discussing it after reading only the headlines.
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How are my friends reacting to news articles?: Instead of learning what the rest of the world is talking about, Alirtify could be a platform that focuses on keeping people informed about what their friends are talking about. This can be accomplished by displaying statistics on how many contacts are discussing a news piece right on the news card, which will assist the user focus their attention on specific topics/articles.
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Show me alternate sources and data: Users will be able to acquire a complete view of the article in focus by interweaving links from hot articles from search engines like Google. Furthermore, having the links displayed just below the article gist in the first fold gives users a holistic picture of what's going on around the news story they're reading.
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Showcasing government-backed data regarding the news issue can assist users reach informed judgments about the news story, increasing the impact of the article.
Evaluate
Stakeholder Feedback
On presenting the entire study to the stakeholders, we received the following feedback:
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Contextual Inquiry: Contextual inquiry is a type of ethnographic field study that involves in-depth observation and interviews of a small sample of users to gain a robust understanding of work practices and behaviors. This being their first experience with contextual inquiry methods, they saw the merit in our findings and showed interest in conducting similar studies into other aspects of the app.
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Validity: Having collected data points from a smaller sample of users, the stakeholders saw merit in taking the study forward by building out the prototype as per our design suggestions and using it to conduct user studies on a larger scale to validate our findings.
Kwabena Okrah
Chief Operating Officer (COO)- Alirtify
Working with you and your team from College of Information Studies (UMD iSchool), University of Maryland on our project at Alirtify (Platform - AI / ML / Deep Learning) was very pivotal. I got to experience how human centered design works through your course work.
You helped me understand the importance of UX research and good UI design for its easy adoption by users.
Thank you for the dedication to helping us find answers to our challenges.
Reflection
What did I learn?
This project was my first dive into contextual inquiry with a stakeholder in terms of UX and hence it was overall filled with great learnings.
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Start on the right foot: A good base of research is important to understand the right questions to ask. When working with a small sample set, each data point holds a lot of importance. Having good communication with the team as well as the stakeholder forms the base of the study and its very important to build a strong foundation.
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Trust the process: Following a path to classify the data points and Interpreting user data through affinity mapping, guides the study and gives an insight into what models will help with answering the problem statement. It helped us understand people's cognitive biases and their psychology in approaching news in today's scenario of a world where there is no dearth of sources that are constantly pushing to influence us.
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Team work is dream work: I learned the importance of working with a team of diverse people who check our own biases going into a study and let the collaboration work in a way that benefits the end goal of making the product better.