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Analyzing Interruptibility from the Student Dataset
This master thesis aims at analyzing a dataset collected on smartphones of American students. Of particular focus is when and under which conditions people use their smartphone.
Keywords: Big Data, machine learning, student dataset, interruptibility, human behavior, smartphone
The Dartmouth College in the USA has collected smartphone data of students and has made the dataset publicly available (http://studentlife.cs.dartmouth.edu/dataset.html). To understand, how people use their phone and when people can be interrupted, we would like to analyze this dataset in more depth.
Ideally, you will be able to identify under what circumstances someone is most likely to use a smartphone. Our motivation behind this is to find opportune moments to send messages that are read immediately.
The Dartmouth College in the USA has collected smartphone data of students and has made the dataset publicly available (http://studentlife.cs.dartmouth.edu/dataset.html). To understand, how people use their phone and when people can be interrupted, we would like to analyze this dataset in more depth.
Ideally, you will be able to identify under what circumstances someone is most likely to use a smartphone. Our motivation behind this is to find opportune moments to send messages that are read immediately.
The goal of this master thesis is to understand the conditions under which people are using their smartphone.
You should bring:
- Experience in programming
- Skills or the interest to learn the basics of machine learning
- Interest in Big Data analysis
- Interest in human behavior prediction based on smartphone data
- ETH / UZH students are preferred
The goal of this master thesis is to understand the conditions under which people are using their smartphone.
You should bring:
- Experience in programming
- Skills or the interest to learn the basics of machine learning
- Interest in Big Data analysis
- Interest in human behavior prediction based on smartphone data
- ETH / UZH students are preferred
Please send your application with a short motivation letter (~250 words), transcript of records and CV to Florian Künzler (fkuenzler@ethz.ch).
If you have any further questions or comments, please don't hesitate to contact me.
Please send your application with a short motivation letter (~250 words), transcript of records and CV to Florian Künzler (fkuenzler@ethz.ch).
If you have any further questions or comments, please don't hesitate to contact me.