一种针对Facebook社交网络的数据挖掘方法:以台湾“新排面”为例

Jong-Shin Chen, Chi-Yueh Hsu, Cheng-Ying Yang, Ching-Chuan Wei, Han Guo Ciang
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引用次数: 1

摘要

Facebook在台湾的渗透率是世界上最高的,直到2015年7月,台湾的日用户数达到1300万,人口约为2300万。基于位置的Facebook签到服务是一个热门话题,许多Facebook用户去他们感兴趣的许多签到地点并在那里签到。台湾牛肉面被认为是一道国菜。2011台北国际牛肉节已将台湾牛肉面翻译为新列面。这一命名模仿了从当地语言直译过来的日本寿司或韩国泡菜,突出了独特的文化。通过人类活动中的文化,也会产生相关的Facebook签到地点和签到行为。在本研究中,我们提出了一种收集Facebook签到地点大数据的方法,找出与“新排棉”相关的地点和这些地点的位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A data mining method for Facebook social network: Take “New Row Mian (Beef Noodle)” in Taiwan for example
Facebook penetration rate in Taiwan is the highest in the world, until July 2015 in Taiwan, the number of daily users reached 13 million for approximately 23 million population. Location-based Facebook check-in service is a hot topic, numerous Facebook users go to their interested numerous checkin-in places and check in there. Taiwan beef noodle is considered a national dish. 2011 Taipei International Beef Festival has been Taiwan beef noodle translated as New Row Mian. The naming imitates Japanese Sushi or Korean Kimchi that translated from the local language literal translation, highlighting the unique culture. Through the culture in the human activities, it will also produce the relevant Facebook check-in places and check-in behaviors. In this study, we propose a method to collect the big data of Facebook check-in places, find out the places related to “New Row Mian” and position for these places.
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