A Local-Global LDA Model for Discovering Geographical Topics from Social Media

Micro-blogging services can track users' geo-locations when users check-in their places or use geo-tagging which implicitly reveals locations. This "geo tracking" can help to find topics triggered by some events in certain regions. However, discovering such topics is very challenging because of the large amount of noisy messages (e.g. daily conversations). This paper proposes a method to model geographical topics, which can filter out irrelevant words by different weights in the local and global contexts. Our method is based on the Latent Dirichlet Allocation (LDA) model but each word is generated from either a local or a global topic distribution by its generation probabilities. We evaluated our model with data collected from Weibo, which is currently the most popular micro-blogging service for Chinese. The evaluation results demonstrate that our method outperforms other baseline methods in several metrics such as model perplexity, two kinds of entropies and KL-divergence of discovered topics

A Generalized Recurrent Neural Architecture for Text Classification with Multi-Task Learning

Multi-task learning leverages potential correlations among related tasks to extract common features and yield performance gains. However, most previous works only consider simple or weak interactions, thereby failing to model complex correlations among three or more tasks. In this paper, we propose a multi-task learning architecture with four types of recurrent neural layers to fuse information across multiple related tasks. The architecture is structurally flexible and considers various interactions among tasks, which can be regarded as a generalized case of many previous works. Extensive experiments on five benchmark datasets for text classification show that our model can significantly improve performances of related tasks with additional information from others

Costly Signaling and China's Strategic Engagement in Arctic Regional Governance

In recent years, China has become an increasingly important actor in Arctic regional governance. While Beijing consistently frames its engagement in the region as a strategy of mutually-beneficial cooperation, some Arctic countries have raised significant concerns about its growing economic presence, warning that China may leverage its geopolitical influence to change the existing norms and rules in the polar region. Facing the mounting “China threat” skepticism, what are Beijing's coping strategies to belie concerns? Based on a review of the existing research and government documents, particularly Chinese-language scholarly works and official reports, this article specifically identifies two types of costly signaling approaches employed by China to reduce Arctic countries' distrust. First, China has started to curtail its Arctic investment in oil, gas, and mining while engaging more in sectors that chime well with Western societies' global environmental values, including clean and renewable energy, ecological research that addresses further climatic change associated with global warming, and other environmentally sustainable industries. Second, Beijing has increasingly involved in regional international organizations, such as the Arctic Council, to signal its willingness to exercise state power under institutional constraints. These approaches aim to send a series of costly signals to conventional Arctic states, reassuring them that China is not a revisionist power that pursues hegemony in the region. Taken together, our findings have both scholarly and policymaking implications to understand China's participation in Arctic regional governance

Tensor modules over Witt superalgebras

In this paper, we study the tensor module $P\otimes M$ over the Witt superalgebra $W_{m,n}^+$ (resp. $W_{m,n}$), where $P$ is a simple module over the Weyl superalgebra $K_{m,n}^+$ (resp. $K_{m,n}$) and $M$ is simple weight module over the general linear Lie superalgebra $\mathfrak{gl}(m,n)$. We obtain the necessary and sufficient conditions for $P\otimes M$ to be simple, and determine all simple subquotient of $P\otimes M$ when it is not simple. All the work leads to completion of some classification problems on the weight representation theory of $W_{m,n}^+$ and $W_{m,n}$.Comment: The paper has been accepted for publication in SCIENCE CHINA Mathematic

Starving the Beast: the Effects of China and the United Nations’ Sanctions on North Korean Rason City’s Rice Prices.

Do economic sanctions targeting authoritarian regimes have effects on non-sanctioned goods, especially food commodities? Although there is a large and increasing amount of literature written on the effects of economic sanctions on authoritarian countries, only a handful of them have delved into the collateral damage of economic sanctions. Among these handful of studies, few studies have proposed a clear mechanism of how non-sanctioned goods could also be influenced by economic sanctions targeting authoritarian regimes with relatively isolated economies. In this article, by using of a unique quantitative data set consisting of daily food commodities prices sourced from North Korea Rason City’s black and gray markets along with ten qualitative interviews with Chinese formal and informal business people in October and November 2017, I found that depending on the relationship between the targeted country and its ally which could potentially serve as its sanction buster country, economic sanctions targeting authoritarian countries could have larger negative influence on non-sanctioned goods, especially food commodities, even on countries that have relatively isolated economies. I also found that as for authoritarian countries with isolated economies such as North Korea, foreign goods could flow into the targeted country through both formal and informal (smuggling and illicit trade) trade channels. When sanctions are imposed, the higher demand for foreign goods stimulates the flourish of underground channels, which facilitates the inflow of both non-sanctioned and sanctioned goods into the targeted country’s domestic market from the targeted country’s sanction buster country. However, when the targeted country’s sanction buster country which is economically connected to the targeted country through both formal and informal trade channels also participates in the international community to impose economic sanctions on the targeted country, economic sanctions from the targeted country’s sanction buster country could have negative effects on even non-sanctioned goods because the previous underground channels could be cut (formal channels are also likely to diminish due to economic pressure), hence the inflow of both sanctioned and non-sanctioned goods could be prohibited. Combined these findings, I propose a unique method to study and measure the effects of economic sanctions on authoritarian regimes with isolated economies: by looking at the effects of economic sanctions on non-sanctioned goods, especially food commodities. Because when economic sanctions are imposed on authoritarian regimes with isolated economies, non-sanctioned goods could follow the flow of sanctioned goods into the targeted country through informal trade channels, hence we can monitor whether economic sanctions do have negative effects on sanctioned goods or not by looking at sanctions’ effects on non-sanctioned goods: if non-sanctioned goods are in fact immune to economic sanctions and remain non-influenced by economic sanctions, then it is likely that underground channels still remain active, which provides potential valid opportunities for informal traders to smuggle sanctioned goods into the targeted country, and hence eventually bust sanctions. On the other hand, if economic sanctions are proved to have larger effects even on non-sanctioned goods, then this phenomenon suggests that underground channels have already been cut and hence the underground flow of sanctioned goods are likely to have been sufficiently prohibited

THE EFFECT OF TRUST ON INFORMATION DIFFUSION IN ONLINE SOCIAL NETWORKS

online social networks have a explosive growth in recent years and they provide a perfect platform for information diffusion. Many models have been given to explore the information diffusion procedure and its dynamics. But the trust relationship and memory effect are ignored. Based on the complex network theory, The information diffusion model is proposed and the network users, considered as agents, are classified into susceptible, infected and recovered individuals. The users’ behaviour rule and diffusion process are designed. The proposed agent-based model is tested by simulation experiments in four different complex networks: regular network, small world network, random network and scale-free network. Moreover, the effect of four immunization strategies are explored. The research results show that the influence of users’ trust relationship on different networks is varied, and the vertex weight priority immunization strategy is the best one in all four networks