ConStance: Modeling Annotation Contexts to Improve Stance Classification

Manual annotations are a prerequisite for many applications of machine learning. However, weaknesses in the annotation process itself are easy to overlook. In particular, scholars often choose what information to give to annotators without examining these decisions empirically. For subjective tasks such as sentiment analysis, sarcasm, and stance detection, such choices can impact results. Here, for the task of political stance detection on Twitter, we show that providing too little context can result in noisy and uncertain annotations, whereas providing too strong a context may cause it to outweigh other signals. To characterize and reduce these biases, we develop ConStance, a general model for reasoning about annotations across information conditions. Given conflicting labels produced by multiple annotators seeing the same instances with different contexts, ConStance simultaneously estimates gold standard labels and also learns a classifier for new instances. We show that the classifier learned by ConStance outperforms a variety of baselines at predicting political stance, while the model's interpretable parameters shed light on the effects of each context.Comment: To appear at EMNLP 201

Fashion retailing – past, present and future

This issue of Textile Progress reviews the way that fashion retailing has developed as a result of the application of the World Wide Web and information and communications technology (ICT) by fashion-retail companies. The review therefore first considers how fashion retailing has evolved, analysing retail formats, global strategies, emerging and developing economies, and the factors that are threatening and driving growth in the fashion-retail market. The second part of the review considers the emergence of omni-channel retailing, analysing how retail has progressed and developed since the adoption of the Internet and how ICT initiatives such as mobile commerce (m-commerce), digital visualisation online, and in-store and self-service technologies have been proven to support the progression and expansion of fashion retailing. The paper concludes with recommendations on future research opportunities for gaining a better understanding of the impacts of ICT and omni-channel retailing, through which it may be possible to increase and develop knowledge and understanding of the way the sector is developing and provide fresh impetus to an already-innovative and competitive industr