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Contributors:
  1. Heinrich Hussmann
  2. Bernd Bischl

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Category: Project

Description: This project serves as the collection of all research, teaching, and development activities, conducted with and around the PhoneStudy Android application. The aim of the PhoneStudy project is the development of smartphone applications, a server infrastructure, and adjacent data-tools for both the efficient collection and analyses of behavioral data in psychology and other sciences.

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Personality Traits Predict Smartphone Usage

Collection of supplemental files for the article.

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Validation of Self-Reported Personality with Mobile Application Usage | Registered: 2016-08-17 21:25 UTC


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Dissertation - Differential Human Factors in User Data

Supplemental Files - Dissertation, Clemens Stachl

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Empirisch-Psychologisches Seminar WS 2017/18 LMU

This is the offical OSF Project for the empiric-psychological seminar II in the winter semester 2017/18. Proudly provided by the department of Psychol...

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Digital footprints of sensation seeking: a traditional concept in the big data era

This study investigates the expression of the traditional concept of sensation seeking in the everyday-usage of smartphones. Data used in this study i...

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Repository: Predicting Personality from Patterns of Behavior Collected with Smartphones

This project contains materials, data and code for the study "Predicting Personality from Patterns of Behavior Collected with Smartphones", published ...

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Enter the Wild: Autistic Traits and Their Relationship to Mentalizing and Social Interaction in Everyday Life

Theories derived from lab-based research emphasize the importance of mentalizing for social interaction and propose a link between mentalizing, autist...

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To Challenge the Morning Lark and the Night Owl: Using Smartphone Sensing Data to Investigate Day-Night Behavior Patterns

This osf project includes supplemental materials for the article 'To Challenge the Morning Lark and the Night Owl: Using Mobile Sensing Data to Re-inv...

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Repository: Personality Research and Assessment in the Era of Machine Learning

Project repository for the article of the same name accepted for the special issue on "Behavioral Personality Science in the Age of Big Data" at the E...

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Semantic content outperforms speech prosody in predicting affective experience in naturalistic settings

Many commercial products use algorithms to recognize affect based on speech prosody (i.e., voice acoustics). These algorithms are typically trained on...

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Repository: Age and gender in language, emoji, and emoticon usage in instant messages

Text is one of the most prevalent types of digital data that people create as they go about their lives. Digital footprints of people’s language usage...

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Personality Sensing for Theory Development and Assessment in the Digital Age

Data files and R scripts to reproduce results reported in Personality Sensing manuscript

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