Algorithms measure user influence through microblog repost and mentions
User Influence Analysis Based on Blogs
Social and Information Networks
Summary
Internet users share information very quickly, especially on social networks like microblogs. Measuring who has the most influence in spreading information helps governments and businesses understand communication better. The authors created three algorithms that look at how users forward posts and mention others to calculate each user’s influence. They tested their algorithms with real data and found they work well in identifying influential users.
What this means in practice
- •For social media marketers: Identify key users to target for viral marketing campaigns by analyzing forwarding and mention patterns in microblogs.
- •For public relations teams: Locate influential social media users to monitor or engage for managing online reputation and rumor control.
Authors
Xiang Liu, Yan Jia, Rong Jiang, Yong Quan
Abstract
Rumor and word of mouth spread at the same speed as the highway of information diffusion in the age of the internet. Social networks play quite an important role in the huge internet. Nowadays, social networks have become indispensable in our lives, especially for the government and enterprises. A social network becomes a complex information diffusion network with users working as nodes and the relationships between users working as the vehicle. In this paper, we propose three kinds of algorithms for computing user influence based on the behavior of a user's forwarding microblogs and the symbol of @ in microblogs. We evaluate the effectiveness of the algorithms by comparing the results of our work with the training data in the dataset, and in the end, it proves that our algorithms work well.