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HOME > No.26, Sep. 2021 > Using big data to explore the principles of people's online activities globally

Using big data to explore the principles of people's online activities globally

What is different or the same about online human connections Shiori Hironaka
Shiori Hironaka

A research team led by Shiori Hironaka, a project assistant professor in the Department of Computer Science and Engineering at Toyohashi University of Technology, has collected big data on social media across 10 countries and analyzed the relationship between the connections people make online and their behavior. As a result, they found that the follow ratio, which reflects the behavior of users, is common in each country. We believe that finding common features and differences in data that reflect the diversity of society will lead to the utilization of data that is tailored to the differences in each culture, such as marketing and effective information dissemination

The team collected data on the activities of more than 4,000,000 Twitter users in ten countries (Japan, the U.S.A., Brazil, the U.K., Philippines, Turkey, Indonesia, India, Mexico, and Saudi Arabia) and statistically analyzed the online relationships between the connections and behaviors of users. This is the first analysis of its kind in the world.

As more and more people use social media, ever increasing efforts are being made to use social media data for various surveys and analyses. This is because it is felt that social media data can provide an indirect perspective on the condition of society. However, even if the data on social media is gathered in identical fashion, the nature of the data will still vary by country due to cultural differences and other factors. This is because user behaviors are generally considered to reflect the cyberculture of the group to which they belong. Therefore, if we are to make effective use of social media data for research purposes, we should first try to understand its characteristics.

In this study, we focused on the proximity of users to each other's activity areas and analyzed the connections among users. This is because we believe that the purpose of social media use is closely related to the proximity of activity areas between the people connected on social media. For example, users who use social media to interact with friends are more likely to be close to each other, while users who use social media to post about celebrities or subscribe to news are less likely to be close to each other. We examined the relationship between the proximity of the area of activity and the behavior of users on social media, and compared the characteristics of each country.

The global action area map shows geographical disparities in the use of social media despite worldwide utilization.
The global action area map shows geographical disparities in the use of social media despite worldwide utilization.

As a result, we found a common feature among the 10 countries that is related to the proximity of the user's area of activity. This characteristic is called the follow ratio, which is the ratio of the number of accounts a user is following to the the number of followers of the user themself. A user with a large follow ratio is considered to be a subscription-oriented user. We also found that the longer the user's profile is, the farther from home the action area tends to be, but this finding was not replicated across all ten countries.

Essentially, data on social media connections can express information about users around the world in the same way. However, this may not ensure the expected precision for such functions as friend recommendations and attribute estimations as the nature of the data individually differs due to cultural differences. The characteristics identified by this analysis are expected to help provide the best information to users of different countries and cultures.

For future research, the aim of the research team will be to examine the characteristics of social media big data in more detail, so as to clarify the cultural differences in the use of social media, and to contribute to the development of the next-generation social media.
This research project was sponsored by JPMJMI20B4, a JST-Mirai Program.


Shiori Hironaka, Mitsuo Yoshida and Kyoji Umemura (2021).
Cross-Country Analysis of User Profiles for Graph-Based Location Estimation.
IEEE Access, doi: 10.1109/ACCESS.2021.308652.


廣中 詩織

豊橋技術科学大学情報・知能工学系 廣中詩織特任助教の研究チームは、ソーシャルメディア上で世界10カ国にわたるビッグデータを収集し、人々がオンライン上で作るつながりとふるまいとの関係を分析しました。その結果、ユーザーのふるまいを反映するフォロー比が各国で共通するという特徴を発見しました。社会の多様性が反映されたデータの中で、共通の特徴や違いを見つけることは、それぞれの文化の違いに合わせたデータの活用、例えばマーケティングや効果的な情報発信等につながると考えています。








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Researcher Profile

Shiori Hironaka
Name Shiori Hironaka
Affiliation Department of Computer Science and Engineering
Title Project Assistant Professor
Fields of Research Social Network Analysis, Computational Social Science
National Institute of Technology,
Tokuyama College