Data analysis for understanding social networks in Singapore

• Main Author: Liauw, Siew Guek.
• Other Authors: Xiao Gaoxi
• Format: Final Year Project
• Language: English
• Published: 2011
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer applications::Social and behavioral sciences
• Online Access: http://hdl.handle.net/10356/45973
• Institution: Nanyang Technological University

There is growing theoretical literature on how social networks may affect the spread of directly transmissible infectious diseases. Hence, gaining knowledge of social contact patterns is fundamental to designing effective control strategies for communicable diseases, ranging from a flu pandemic to tuberculosis, to recurrent epidemics. This study aims to understand the role of social networks in shaping disease transmission during a pandemic outbreak in Singapore. The data for this study collected through the use of diary styled survey questionnaires. Each participant had to record his/her social contacts in three different days including one weekday and two weekends or one weekend and two weekdays. Respondents were asked to note down the age, gender of each individual they had a conversation with over the period of three different days and in which social context (such as home, school, work, transportation and others) that conversation took place as well as the duration of each social interaction. The data were organized in a hierarchical fashion, with contacts classified into either physical (skin-to-skin touching) or non-physical (conversational only) contacts based on each age group. The data were entered into text (.txt) or data (.dat) files and statistical analysis was performed using R program. This study found no significant difference in the total number of recorded contacts with regard to the gender of the participants. However, it suggests that people mix substantially more with their own age groups. From the findings, it was evident that the contact patterns observed over the different weekdays had a significant impact on the various characteristics being studied.