A reaction to a product in a store or an assignment in the classroom can tell a lot about the effectiveness of the advertising or the learning method. These reactions can be studied using facial expression analysis, a research method which looks at the facial expression of a person to determine their emotional reaction to some sort of cue. Of course, facial expression analysis is not only limited to these settings – anywhere there is human interaction (with another human or with an object), there is the potential to gain valuable insight on consumer behaviors, emotional reactions, and much more.
FaceReader is software for automated analysis of facial expressions, which gives an objective assessment of a person’s emotion. It can increase the accuracy and reliability of research using facial expression analysis, and make data collection more effective and efficient. On our Behavioral Research Blog, we have published numerous blogs where FaceReader was used for facial expression analysis. Here are a few of them:
- Terzis et al. discovered that empathetic and emotional feedback helped make e-learning easier. They used an avatar which emulated the student’s emotional response to an assessment if the FaceReader analysis and the human judges’ analysis matched. The empathetic avatar would match the emotion and then encourage the student. Students with the avatar found the material as easier to learn and more enjoyable and useful than those without the avatar. Read more...
- Relational Agents (RA) are human-like avatars on the computer that are used to interact with humans. These RAs promote social bonds forming over the long term. The avatar created can be used in many ways, such as in video games, health care, or even teaching. Learn more!
- Advertisements are designed to make us react to them. Lewinski et al. showed that specific patterns of facial expressions can partially explain the effectiveness of the advertisement in amusing persuasive video stimuli. These researchers used FaceReader to analyze facial reactions to three videos with different levels of how amusing they were. Interested? Read more...
- An objective assessment can often be more accurate than even the participant’s personal assessment. Danner et al. tested people’s reactions to different orange juices and used FaceReader to analyze their emotional state. To read about the results, click here.
- Drape et al. explored technology integration in the classroom. To do this, they used numerous techniques including observations, qualitative interviews, and facial expression analysis. Facial expression analysis was done with FaceReader to analyze non-verbal behavior of the students when they watched a video on their computer. Click here to learn more.