Personal and Ubiquitous Computing

, Volume 19, Issue 2, pp 425–444 | Cite as

EmoSnaps: a mobile application for emotion recall from facial expressions

  • Evangelos Niforatos
  • Evangelos Karapanos
Original Article


We introduce EmoSnaps, a mobile application that captures unobtrusively pictures of one’s facial expressions throughout the day and uses them for later recall of her momentary emotions. We describe two field studies that employ EmoSnaps in an attempt to investigate if and how individuals and their relevant others infer emotions from self-face and familiar face pictures, respectively. Study 1 contrasted users’ recalled emotions as inferred from EmoSnaps’ self-face pictures to ground truth data as derived from Experience Sampling. Contrary to our expectations, we found that people are better able to infer their past emotions from a self-face picture the longer the time has elapsed since capture. Study 2 assessed EmoSnaps’ ability to capture users’ experiences while interacting with different mobile apps. The study revealed systematic variations in users’ emotions while interacting with different categories of mobile apps (such as productivity and entertainment), social networking services, as well as direct social communications through phone calls and instant messaging, but also diurnal and weekly patterns of happiness as inferred from EmoSnaps’ self-face pictures. All in all, the results of both studies provided us with confidence over the validity of self-face pictures captured through EmoSnaps as memory cues for emotion recall, and the effectiveness of the EmoSnaps tool in measuring users’ momentary experiences.


Experience Sampling Method (ESM) Emotion self-reporting Day Reconstruction Method (DRM) Experience reconstruction User experience (UX) evaluation 



This work was conducted in the frames of Logica Service Design Lab with support of Knowledge + incentive system in Madeira, Portugal. The authors also acknowledge the financial support of the Future and Emerging Technologies (FET) programme within the 7th Framework Programme for Research of the European Commission, under FET Grant Number: 612933.


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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Faculty of InformaticsUniversity of LuganoLuganoSwitzerland
  2. 2.Madeira Interactive Technologies InstituteFunchalPortugal

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