In Human-Computer Interaction (HCI) research, awareness of how to address diversity is increasing. For example, the number of published papers that offer information on different diversity dimensions has significantly increased [2]. Designers and developers aim to be aware of the different types of their technology users to ensure that no individual or community is harmed…… Continue reading Towards Designing a More Inclusive Technology
Category: Customer segmentation
Cross-Platform Social Media Studies: Five Advantages And Five Disadvantages
There is a growing body of research on social networks, including studies that focus on how social networks are used on different platforms, how users move between platforms, and how platforms are integrated into the overall media diet of users. A study by the Pew Research Center found that social networks are used by most…… Continue reading Cross-Platform Social Media Studies: Five Advantages And Five Disadvantages
Which engagement level can we predict better on Instagram? A classification approach
In social media, likes and comments are key metrics for success. If you can predict how many likes and comments a post will get, you can better manage your content strategy and create content that resonates with your audience. There are a few ways to build a prediction model for the number of likes. In…… Continue reading Which engagement level can we predict better on Instagram? A classification approach
Demystifying Language Models: The Case of BERT’s Usage in Solving Classification Problems
Newcomers to the field of Artificial Intelligence (AI) often see the term ‘language model’ tossed around when discussing Natural Language Processing (NLP) tasks without any proper clarification of its importance and usage in solving real-world problems. So, this tutorial blogpost aims at demystifying language models by defining what a language model is, describing the common…… Continue reading Demystifying Language Models: The Case of BERT’s Usage in Solving Classification Problems
Log Odds Ratio: Going Beyond Simple Term Frequencies to Characterize Textual Categories
Gaining insights from text-based data can be a daunting task, even when the data is labeled with ground truth categories and ready for usage in machine learning tasks.Researchers often rely on simple methods like the frequency of words in each category to understand the collection’s characteristics. However, this approach is not always insightful, as term…… Continue reading Log Odds Ratio: Going Beyond Simple Term Frequencies to Characterize Textual Categories
VLCP: A four-level framework for social media user engagement metrics
When evaluating the performance of social media content, user engagement is a key performance indicator (KPI). Specifically, the interaction by the user with the content, such as viewing, liking, commenting, and sharing. From the mindset of a social media content producer, users with more public expressiveness of their interest have higher impactful engagement with the…… Continue reading VLCP: A four-level framework for social media user engagement metrics
The Illusion of Data Validity: Why Numbers About People Are Likely Wrong
This reflection article addresses a difficulty faced by scholars and practitioners working with numbers about people, which is that those who study people want numerical data about these people. Unfortunately, time and time again, this numerical data about people is wrong. Addressing the potential causes of this wrongness, we present examples of analyzing people numbers,…… Continue reading The Illusion of Data Validity: Why Numbers About People Are Likely Wrong
When mere correlations are not enough: The Granger Causality test
In most data science-related problems, datasets consist of multiple variables, in which independent variables might depend on other independent variables. When the variables in datasets represent observations at different times, we call this dataset a time series set. The time interval in these data sets may be hourly, daily, weekly, monthly, quarterly, annually, etc. One…… Continue reading When mere correlations are not enough: The Granger Causality test
SegmentSizeEstimator, a research tool of the Acua Platform
Wondering what factors contribute to high levels of online engagement? In our research, we have found that one of the most reliable predictors of level of engagement for an ad, online content, or social media post for a given channel is simply size of the target population. For example, we’ve ranked viewers of YouTube channels…… Continue reading SegmentSizeEstimator, a research tool of the Acua Platform
Engineers, Aware! Commercial Tools Disagree on Social Media Sentiment
For segmentation, one often need to use sentiment analysis services. Large commercial sentiment analysis tools are often deployed in software engineering due to their ease of use. However, it is not known how accurate these tools are, and whether the sentiment ratings given by one tool agree with those given by another tool. We use…… Continue reading Engineers, Aware! Commercial Tools Disagree on Social Media Sentiment