Optimizing the User Experience of Mobile Instant Messaging
The general goal of this project is to learn models that predict opportune (resp. non-interrupting) moments to notify users on received mobile instant messages. These models aim at maximizing users’ receptivity towards messages. Receptivity is defined as users’ subjective overall reaction to an interruption, encompassing their interruptibility and the experience of the interruption. According to this definition, interruptibility depends on the context of a user (location, time of day, etc.) and the experience of interruption on the sender and the content of a message. To be able to learn predictive models in this context, we run a data collection study using an Android app to collect information about the context of a user at the moment of message delivery as well as the sender and the content of a message.
Research found out that factors like peer pressure or the fear of missing out on something causes users to immediately react on messages although delivered at inconvenient moments. As a result, user behavior often differs from user intention. Related work overcomes this problem by polling users’ for their true receptivity towards an incoming message, increasing user interruptions and information load. In contrast, we hypothesize that in expectation the empirical behavior of users towards incoming messages will go towards the true, intended user behavior. To build a model based on that assumption, a large sample size per user is necessary. For this reason, we try to exploit user similarities to build robust models that better predict users’ receptivity given their context.
In order to be able to train models which predict opportune (resp. non-interrupting) moments to notify users about received mobile instant messages, we conduct a data collection study. If you want to participate you can install MSGSTAZ from Google's Play Store. For detailed information on the study, i.e. what data is collected, how data is anonymized, etc., please follow this link.
MSGSTAZ is an Android app which provides statistics and other features centered around mobile messaging. It supports the messengers WhatsApp, Facebook Messenger, Google Hangouts, Viber and Skype. It is used to collect data about users’ mobile instant message behavior for the research project Intelligent Messages. MSGSTAZ offers the following features:
The statistics of MSGSTAZ enable you to see how much messages you received in a certain time period. It allows you to dig into details about how much messages you received from a specific friend, group or messenger. MSGSTAZ uses HelloCharts to display diagramms.
Global Mute is a feature which enables you to mute one of your contacts accross messengers installed on your smartphone. You can mute a contact by clicking the speaker on the top right in the detail dialog.
"Make Them Aware"
MSGSTAZ allows you to share statistics via applications installed on your smartphone. You can use this feature to gently make friends aware of spamming you, for example.