DocumentCode :
652121
Title :
Characterizing the Performance and Behaviors of Runners Using Twitter
Author :
Qian He ; Agu, Emmanuel ; Strong, Diane ; Tulu, Bengisu ; Pedersen, Peder
Author_Institution :
Dept. of Comput. Sci., Worcester Polytech. Inst., Worcester, MA, USA
fYear :
2013
fDate :
9-11 Sept. 2013
Firstpage :
406
Lastpage :
414
Abstract :
Running is a popular physical activity that improves physical and mental well being. Unfortunately, up-to-date information about runners´ performance and psychological well being is limited. Many questions remain unanswered, such as how far and how fast runners typically run, their preferred running times and frequencies, how long new runners persist before dropping out, and what factors cause runners to quit. Without hard data, establishing patterns of runner behavior and mitigating challenges they face are difficult. Collecting data manually from large numbers of runners for research studies is costly and time consuming. Emerging Social Networking Services (SNS) and fitness tracking devices make tracking and sharing personal physical activity information easier than before. By monitoring the tweets of a runner group on Twitter (SNS) over a 3-month period, we collected 929,825 messages (tweets), in which runners used Nike+ fitness trackers while running. We found that (1) fitness trackers were most popular in North America (2) one third of runners dropped out after one run (3) Over 95% of runners ran for at least 10 minutes per session (4) less than 2% of runners consistently ran for at least 150 minutes a week, which is the level of physical activity recommended by the CDC (5) 5K was the most popular distance.
Keywords :
information retrieval; medical computing; psychology; social networking (online); sport; CDC; Nike+ fitness trackers; North America; SNS; Twitter; data collection; fitness tracking devices; mental wellbeing improvement; personal physical activity information sharing; personal physical activity information tracking; physical activity; physical wellbeing improvement; runner behavior characterization; runner group; runner performance characterization; runner performance information; runner psychological wellbeing information; running frequencies; running times; social networking services; tweets messages; tweets monitoring; Cities and towns; Global Positioning System; Monitoring; Portable media players; Sensors; Twitter; Twitter; data analysis; information retrieval; physical activity; running; social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Healthcare Informatics (ICHI), 2013 IEEE International Conference on
Conference_Location :
Philadelphia, PA
Type :
conf
DOI :
10.1109/ICHI.2013.56
Filename :
6680503
Link To Document :
بازگشت