Intrinsic Correlation with Betweenness Centrality and Distribution of Shortest Paths

Determinants of multimodal fake review generation in China's E-commerce platforms

This paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human-environment interaction hypothesis. Applying survey data from users of China's three leading E-commerce platforms (Taobao, Jingdong, and Pinduoduo), we adopt structural equation modeling, machine learning technique, and Bayesian complex networks analysis to perform factor identification, path analysis, feature factor importance ranking, regime division, and network centrality analysis of full sample, male sample, and female sample to reach the following conclusions: (1) platforms' multimodal recognition and governance capabilities exert significant negative moderating effects on merchants' information behavior, while it shows no apparent moderating effect on users' information behavior; users' emotional venting, perceived value, reward mechanisms, and subjective norms positively influence multimodal fake review generation through perceptual behavior control; (2) feature factors of multimodal fake review generation can be divided into four regimes, i.e., regime 1 includes reward mechanisms and perceived social costs, indicating they are key feature factors of multimodal fake review generation; merchant perception impact is positioned in regime 2, signifying its pivotal role in multimodal fake review generation; regime 3 includes multimodal recognition and governance capabilities, supporting/disparaging merchants, and emotional venting; whereas user perception impact is positioned in regime 4, indicating its weaker influence on multimodal fake review generation; (3) both in full sample, male sample, and female sample, reward mechanisms play a crucial role in multimodal fake review generation; perceived value, hiring review control agency, multimodal recognition and governance capabilities exhibit a high degree of correlation; however, results of network centrality analysis also exhibit heterogeneity between male and female samples, i.e., male sample has different trends in closeness centrality values and betweenness centrality values than female sample. This indicates that determinants influencing multimodal fake review generation are complex and interconnected.

Unraveling the effect of added microbial inoculants on ammonia emissions during co-composting of kitchen waste and sawdust: Core microorganisms and functional genes

Despite the role of microorganisms in nitrogen biotransformation has been extensively explored, how microorganisms mitigate NH₃ emissions in the transformation of nitrogen throughout the composting system is rarely addressed. The present study explored the effect of microbial inoculants (MIs) and the contribution of different composted phases (solid, leachate, and gas) on NH₃ emissions by constructing a co-composting system of kitchen waste and sawdust with and without the addition of MI. The results showed that NH₃ emissions increased markedly after adding MIs, in which the contribution of leachate ammonia volatilization to NH₃ emissions was most prominent. The core microorganisms of NH₃ emission had a clear proliferation owing to the MIs reshaping community stochastic process. Also, MIs can strengthen the co-occurrence between microorganisms and functional genes of nitrogen to promote nitrogen metabolism. In particular, the abundances of nrfA, nrfH, and nirB genes, which could augment the dissimilatory nitrate reduction process, were increased, thus enhancing NH₃ emissions. This study bolsters the fundamental, community-level understanding of nitrogen reduction treatments for agricultural.