Inferring friendship network structure by using mobile phone data.
نویسندگان
چکیده
Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.
منابع مشابه
Inferring Social Network Structure using Mobile Phone Data
We analyze 330,000 hours of continuous behavioral data logged by the mobile phones of 94 subjects, and compare these observations with selfreport relational data. The information from these two data sources is overlapping but distinct, and the accuracy of self-report data is considerably affected by such factors as the recency and salience of particular interactions. We present a new method for...
متن کاملMeasuring social relations with multiple datasets
Because people have different levels of engagement with each other, measuring social relations is difficult. In this work, we propose a method of measuring social relations with multiple datasets and demonstrate the differences with empirical evidence. Our empirical findings demonstrate that people use different communication media channels differently. Therefore, we suggest that in order to un...
متن کاملNurturing Social Networks Using Mobile Phones
Youngsters maintain contact with each other through social-networking websites. We propose new ways of nurturing contacts by monitoring users’ activity with mobile phones (i.e., by monitoring text messages, phone calls, and encounters captured by Bluetooth). We show that, based on user’s activity, one is able to recommend new friends, track health of friendships (and alert users they may be neg...
متن کاملPersian Phone Recognition Using Acoustic Landmarks and Neural Network-based variability compensation methods
Speech recognition is a subfield of artificial intelligence that develops technologies to convert speech utterance into transcription. So far, various methods such as hidden Markov models and artificial neural networks have been used to develop speech recognition systems. In most of these systems, the speech signal frames are processed uniformly, while the information is not evenly distributed ...
متن کاملElectromagnetic Fields of Mobile Phone Jammer Exposure on Blood Factors in Rats
Background: The increasing demand for using mobile phones has led to increasing mobile phone jammers as well. On the other hand, reports show that exposure to electromagnetic field causes an increase in the incidence of diseases such as leukemia, cancer, depression and failure in pregnancy outcomes; therefore, the aim of this study is to investigate the effects of exposure to electromagnetic fi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Proceedings of the National Academy of Sciences of the United States of America
دوره 106 36 شماره
صفحات -
تاریخ انتشار 2009