scholarNetwork is a python package for crawling and visualizing the co-author network of Google Scholar.
Selected Publications
The Hidden Shape of Stories Reveals Positivity Bias and Gender Bias
To capture the shape of stories is crucial forunderstanding the mind of human beings. In this research, we use word emdeddings methods, a widely used tool in natural language processing and machine learning, in order to quantify and compare emotional arcs of stories over time. Based on trained Google News word2vec vectors and film scripts corpora (N =1109), we form the fundamental building blocks of story emotional trajectories. The results demonstrate that there exists only one universal pattern of story shapes in movies. Furthermore, there is a positivity and gender bias in story narratives. More interesting, the audience reveals a completely different preference from content producers.
arXiv:1811.04599v1 [cs.CL], 2018.
计算传播学导论
Introduction to Computational Communication (In Chinese 计算传播学导论) now available on for pre-order! http://product.dangdang.com/25581097.html. With the development of digital media, data-driven journalism, computational advertising, and media recommendation systems become a worldwide trend. At the same time, the study of information flow in online social networks has attracted a lot of attention; machine learning, as well as data science have made a big leap forward. Put together, all of these factors discussed above speed up the tide of computational communication research.
北京师范大学出版社, 北京, ISBN: 9787303241200, 2018.
The Collective Direction of Attention Diffusion
We suggest that the tree-like, stable structure of clickstream networks reveals the time-sensitive preference of users in online browsing. To test our assumption, we discuss three models on individual browsing behavior, and compare the simulation results with empirical data.
In Scientific Reports 6, Article number: 34059 (2016) doi:10.1038/srep34059, 2016.
