Online Social Networks (OSNs), such as Facebook, Twitter, Instagram, YouTube, and TikTok, have become increasingly popular in the last decade and are now an integral part of many people’s daily lives. According to Meta reports, Facebook has 2.06 billion daily active users with an increase of 5% year-over-year and 3.03 billion monthly active users in 2023, and Facebook users spend an average of 33 minutes daily. Twitter currently has more than 237.8 million daily active users, and 556 million monthly active users. There are 500 million tweets per day, which adds up to 15 billion tweets in one month. For Instagram, there are 2 billion monthly active users and 500 million daily active users, and Instagram users spend more than 28 minutes per day on average. In addition, over 2.7 billion people access YouTube once a month, making it one of the most popular social media in the world, and YouTube Premium has reached 80 million subscribers in 2022. TikTok has 1.1 billion monthly active users, spending an average of 95 minutes on the app daily, and there are over 100 billion average monthly video views on TikTok.
Also, social networks and human computation have brought new applications to natural language processing (NLP), mobile computing, multimedia, data mining, and human-centered computing. For example, NLP and data mining in social networks enable researchers to understand the trend, sentiment, influence, and opinions of the users in social networks. By considering the social comments, links, and interactions, the ranking and recommendations of multimedia contents become more precise and effective. Moreover, by examining the social relations of users with mobile devices, researchers can exploit location-based and contextual information embedded with mobile social networks to create useful insights for community discovery, group mobility patterns, and location-based viral marketing. Finally, human-centered computing can leverage social networks to build systems for problem-solving in distributed environments. The social and human factors in these areas indeed enable many new applications, and new challenges arise due to the additional dimension necessary to be carefully examined.
Therefore, it is envisaged that the direction of this program, Social Networks and Human-Centered Computing, is crucial from the perspectives of academia and industry. National Tsing Hua University (NTHU), National Chengchi University (NCCU), and Academia Sinica jointly establish the TIGP on Social Networks and Human-Centered Computing (SNHCC) in 2012. SNHCC are new important applications and technologies that have been rapidly developing in recent years. The TIGP SNHCC program can cultivate Taiwanese and international talents in related areas to the program, strengthen innovative potential, and enhance the level of academic research. NTHU, NCCU and Academia Sinica will co-play leading and supervisory roles, and provide research resources and equipment. Additionally, the participating scholars of these three institutions will be jointly responsible for teaching activities, supervising research, and guiding international graduate students.
|Coordinator:||Dr. Ku, Lun-Wei 古倫維研究員
Institute of Information Science
|Program Assistant :||Ms. Chia-chien Hsiao 蕭佳倩小姐|
|TEL:||886-2-2788-3799 ext. 2303|