This paper presents the results of an exploratory quantitative analysis of gendered contributions to the online mapping project OpenStreetMap (OSM), in which previous research has identified a strong male participation bias. On these grounds, theories of representation in volunteered geographic information (VGI) have argued that this kind of crowdsourced data fails to embody the geospatial interests of the wider community. The observed effects of the bias however, remain conspicuously absent from discourses of VGI and gender, which proceed with little sense of impact. This study addresses this void by analysing OSM contributions by gender and thus identifies differences in men’s and women’s mapping practices. An online survey uniquely captured the OSM IDs as well as the declared gender of 293 OSM users. Statistics relating to users’ editing and tagging behaviours openly accessible via the ‘how did you contribute to OSM’ wiki page were subsequently analysed. The results reveal that volumes of overall activity as well editing and tagging actions in OSM remain significantly dominated by men. They also indicate subtle but impactful differences in men’s and women’s preferences for modifying and creating data, as well as the tagging categories to which they contribute. Discourses of gender and ICT, gender relations in online VGI environments and competing motivational factors are implicated in these observations. As well as updating estimates of the gender participation bias in OSM, this paper aims to inform and stimulate subsequent discourses of gender and representation towards a new rationale for widening participation in VGI.

As UK cities and towns become increasingly ethnically and culturally diverse, researchers have tuned into how people inhabit multiculturalism. Ethnographic approaches have focused on the kind of togetherness that people generate as they go about their everyday lives, observing the affective textures of interactions and happenings of the here and now in granular detail. Missing from these accounts is what crowdsourced data might add to understandings of how multicultural places are experienced. What is vital about this kind of data is that it is ‘big’, involving a diversity of voices similarly intent on messaging their experiences, presenting opportunities to scale up the affect of encounters and to quantify what is difficult to qualify. This paper brings Digital Geographies into conversation with research on everyday multiculturalism to examine qualitatively and quantitatively how social media use folds into and expresses various practices of sociality and connection. Our paper involves Twitter, Nando’s and the city of Leicester in the UK to challenge and advance ways of understanding everyday multiculturalism in an era of global migration and ethnically complex populations.

The way that virtual reality recreates space and environments on a variety of scales and situations, renders it of immediate interest to geographers interested in the relationship between people and their environments. In this methodological chapter, we demonstrate how VR mediates the methodological process of capturing affect. Reflecting on our experiences during the Mapping Multiculture project, the chapter reflects on VR as an immersive sensory experience, the processes of dislocation between virtual and physical, the physical challenges that arise, and how removing the researcher gaze shapes the research. We argue that VR offers tremendous opportunities for researchers interested in examining a range of geographic topics, not least the affectual and emotional underpinnings of the relationship between people and place.

Events are the driving force behind social media, whether we try to create them or keep up with them. A wide range of studies has focused on how content from social media can be used to detect, model and predict events and identify key topics of discussion. At the same time, very limited attention has been given so far to the quantitative study of the everyday, which has fascinated qualitative human geography research in the past few decades. That is partly due to the lack of a formal definition of what constitutes the everyday. In this paper, we aim to advance our understanding of the everyday, not by reducing it to any kind of definition but by bringing it into view through a quantitative analysis. We hypothesise that the by-products of current methods focused on event detection might be used to quantitatively explore everyday geographies as represented through Twitter data. We consider the use of both statistical approaches based on term frequency and state-of-the-art large language models, and we conduct a case study on content posted on Twitter and geolocated in the city of Leicester. Our paper makes two key advances for research concerned with the everyday and the analysis of geographic information. First, we illustrate how large language models combined with spatial analysis and visualisation can foster the study of everyday geographies, providing an insight into the still elusive concept of the everyday, representing what other approaches to the everyday have struggled to qualify. Secondly, we showcase the potential held by large language models and visual analytics in democratising sophisticated natural language processing and thus providing new tools for research in human geography.

ISHS III WOCMAP Congress on Medicinal and Aromatic Plants - Volume 2: Conservation, Cultivation and Sustainable Use of Medicinal and Aromatic Plants SUSTAINING THE HARVEST: CHALLENGES IN MAP PRODUCTION AND MARKETS