The temporal evolution of the normalized web distance
本文研究归一化网络距离（NWD）随时间的变化能否作为衡量社会赋能进程的元数据技术，并以墨西哥Wirikuta在线运动为例，展示了1994年至2013年间关键词与分类词之间NWD的演化趋势。
Purpose The purpose of this paper is to assess whether the temporal evolution of the normalized web distance ( NWD ) between significant terms concerning, e.g., a case of online activism can be used as a meta-data technique to measure evolution over time of, e.g., progress or decline of social empowerment. Design/methodology/approach The NWD between two terms has been identified as a quantitative measure for semantic proximity, ascertaining a defining relation between them. A trend analysis is made by performing on the internet a time window restrained series measurement of NWD of all combinations of key-terms and classifier-terms. Case defining key-terms, positive and negative discourse polarizing classifier-terms, and neutral classifier-terms for negative control need to be determined by discourse analysis of information on a targeted case. An example of NWD evolution from 1994 until 2013 is presented to measure the empowerment effects of the Wirikuta online movement on the Huichol people in Mexico. Findings The application of the NWD temporal evolution method to the Wirikuta case shows a slight but significant semantic change of the key-terms with respect to some of the positive and negative classifier-terms. The neutral classifier correctly shows no significant distance variation, as required for valid application of the method. The method provides indications for a complex image of empowerment of the Huichol identity. Research limitations/implications The accuracy of the method is limited due to short-term and between-user variability of the search tool’s page counts. More reliable access to a web-index will be required for more accurate NWD -based trend analysis. Practical implications The monitoring of temporal NWD evolution provides a potential tool for more comprehensive trend description compared to classical frequency based methods. Originality/value Trend analysis is key to internet research, to which the temporal NWD method provides an innovative contribution.