Mobile immobility: an exploratory study of rural women’s engagement with e-commerce livestreaming in China

Based on our fieldwork in Yunnan Province and Ningxia Hui Autonomous Region, this paper explores the different ways in which Chinese rural women engage with the rising industry of e-commerce livestreaming related to agricultural products and villages. Our analytical framework is informed by feminist political economy, which pays heed to the gendered social settings, operation of power, and entanglement between women’s domesticity and productivity that underpin people’s economic activities. We argue that Chinese rural women’s simultaneous empowerment and disempowerment by e-commerce livestreaming are characterized by “mobile immobility”, a term inspired by Wallis’s (2013) research on rural women’s technological empowerment by mobile phones a decade ago. On the one hand, this latest form of e-commerce has created an apparently accessible path for rural women, who tend to be geographically immobile, to achieve social mobility by becoming professional webcasters and/or vloggers. On the other hand, this enablement is in fact classed, aged, and preconditioned on in-laws’ support and willingness to share these women’s domestic duties, which are not guaranteed. The urban-oriented digital economy of e-commerce livestreaming capitalizes on rural young women’s femininity, docile bodies and labor as well as the reproductive labor performed by their family members at the microlevel, reinforcing the urban–rural disparity at the macrolevel. The paper ends with reflections on the role of information and communication technologies and e-commerce in the development of rural China

A PatchMatch-based Dense-field Algorithm for Video Copy-Move Detection and Localization

We propose a new algorithm for the reliable detection and localization of video copy-move forgeries. Discovering well crafted video copy-moves may be very difficult, especially when some uniform background is copied to occlude foreground objects. To reliably detect both additive and occlusive copy-moves we use a dense-field approach, with invariant features that guarantee robustness to several post-processing operations. To limit complexity, a suitable video-oriented version of PatchMatch is used, with a multiresolution search strategy, and a focus on volumes of interest. Performance assessment relies on a new dataset, designed ad hoc, with realistic copy-moves and a wide variety of challenging situations. Experimental results show the proposed method to detect and localize video copy-moves with good accuracy even in adverse conditions