2018 Impact factor 3.262

EPJ Data Science Highlight - Using social media for large-scale studies of gender differences

Photo from Pixabay, CC0 public domain.
Photo from Pixabay, CC0 public domain.

Social networks capture data about most aspects of the daily lives of millions of people around the world. The analysis of this rich and ready-available source of information can help us better understand the complex dynamics of society.

In a recent article published in EPJ Data Science the authors propose the use of location-based social networks to study the activity patterns of different gender groups, which they summarise in a guest post on the SpringerOpen blog.

Gender differences have a subjective nature and may vary greatly across cultures, making them challenging to explain. Indeed, over the past decades, this topic has received a lot of attention by researchers, but there is still a long way to reach a consensus on the subject.

Traditional ways to study differences between gender groups depend on surveys, which are costly and do not scale up. Moreover, data produced under such conditions are commonly released after long time intervals (e.g., several years). Therefore, the studies cannot quickly capture changes in the dynamics of societies. Besides, the results from cross-regional gender differences studies are usually available only for large geographic regions, often countries. Thus, even though survey-based studies could be carried out in arbitrarily small regions, such as a city, a neighborhood or even a particular venue (e.g., a university or a mall), information about gender differences at such fine spatial granularities is not easily available.

We present another way to obtain and explore similar data that could help the study of global gender differences. To map individual preferences, we propose using publicly available data from location-based social networks (LBSNs). This is interesting because when specific users of LBSN check into a specific location they express their preference for this type of place. LBSNs are accessible almost everywhere by anyone and thus allow data collection from the entire world at a much lower cost compared to traditional surveys.

Continue reading here.

M. Strohmaier