This article presents an overview and initial results of a geoweb analysis designed to provide the foundation for a continued discussion of the potential impacts of 'big data' for the practice of critical human geography. While Haklay's (2012) observation that social media content is generated by a small number of 'outliers' is correct, we explore alternative methods and conceptual frameworks that might allow for one to overcome the limitations of previous analyses of user-generated geographic information. Though more illustrative than explanatory, the results of our analysis suggest a cautious approach toward the use of the geoweb and big data that are as mindful of their shortcomings as their potential.More specifically, we propose five extensions to the typical practice of mapping georeferenced data that we call going 'beyond the geotag': (1) going beyond social media that is explicitly geographic; (2) going beyond spatialities of the 'here and now'; (3) going beyond the proximate; (4) going beyond the human to data produced by bots and automated systems, and (5) going beyond the geoweb itself, by leveraging these sources against ancillary data, such as news reports and census data. We see these extensions of existing methodologies as providing the potential for overcoming existing limitations on the analysis of the geoweb.The principal case study focuses on the widely reported riots following the University of Kentucky men's basketball team's victory in the 2012 NCAA championship and its manifestation within the geoweb. Drawing upon a database of archived Twitter activity -including all geotagged tweets since December 2011-we analyze the geography of tweets that used a specific hashtag (#LexingtonPoliceScanner) in order to demonstrate the potential application of our methodological and conceptual program. By tracking the social, spatial, and temporal diffusion of this hashtag, we show how large databases of such spatially referenced internet content can be used in a more systematic way for critical social and spatial analysis.

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Conspiracy theories have proliferated during the COVID-19 pandemic to provide an explanation for uncontrollable circumstances. Most conspiratorial explanations often ascribe disease to foreigners or as a result of deliberate actions. Through mapping retweets that attribute COVID-19 to a bioweapon or a lab in China, I examine the geography behind a metonymic conspiracy theory.

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The provision of open data by governments at all levels has rapidly increased over recent years. Given that one of the dominant motiva-

Geotagged tweets, Foursquare check-ins and other forms of volunteered geographic information (VGI) play a critical role in numerous studies and a large range of intelligent technologies. We show that three of the most commonly used sources of VGI – Twitter, Flickr, and Foursquare – are biased towards urban perspectives at the expense of rural ones. Utilizing a geostatistics-based approach, we demonstrate that, on a per capita basis, these important VGI datasets have more users, more information, and higher quality information within metropolitan areas than outside of them. VGI is a subset of user-generated content (UGC) and we discuss how our results suggest that urban biases might exist in non-geographically referenced UGC as well. Finally, because Foursquare is exclusively made up of VGI, we argue that Foursquare (and possibly other location-based social networks) has fundamentally failed to appeal to rural populations.

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Online social media has become an integral part of daily life for many Internet users and there are now hundreds of millions utilising these services around the world. Concomitant with this growth of usage is a desire by companies, government agencies, and academics to study and map the data trails left by people using services like Twitter, Flickr, and Facebook. The data shadows and information trails left by users online reveal social, economic, and political processes and practices.Twitter, in particular, is repeatedly used as a repository of social data because of its relatively open network that allows researchers access to almost any information published through the platform. Yet, despite the many studies (both inside and outside of academia) that draw on data from Twitter, there is little scholarship devoted to the geography of Twitter.As a fi rst step, we decided to collect all georeferenced tweets sent between 5 March and 13 March 2012. It is important to point out that georeferenced tweets comprise fewer than 1% of all tweets and it is possible that signifi cant geographic biases exist in where and how people georeference their content (Graham et al, 2012a). We then took a random 20% sample of that dataset: giving us approximately 4.5 million tweets that we spatially joined at the country level.Our graphic illustrates these data as a spatially aware treemap. The size of each block represents the number of tweets emanating from that country and the shading shows the number of geocoded tweets as a proportion of that country's Internet population (ie, it gives us a sense of how likely Internet users are to create geocoded Twitter content).The graphic reveals a large amount of inequality in the geography of content. However, while many other online platforms are characterised by distinct digital divisions of labour in which the Global North is a predominant producer and subject of content (Graham et al, 2011), Twitter displays signifi cantly different geographies.The six largest countries in terms of information production through Twitter are: (1) the United States, (2) Brazil, (3) Indonesia, (4) the United Kingdom, (5) Mexico, and (6) Malaysia. It is interesting to note that only two of the countries on that list are in the Global North and are traditional hubs of the production of codifi ed knowledge.By mapping the distribution of tweets in the world it becomes apparent that Twitter is allowing for broader participation than is possible in most other platforms and media. In other words, it might be allowing for a 'democratisation' of information production and sharing because of its low barriers to entry and adaptability to mobile devices. Similarly barriers to the dissemination of information, such as censorship, are also visible through the small proportion of tweets originating in China (home to the largest population of Internet users in the world).However, more research is undoubtedly necessary to better understand the geography of content on the platform. Our sample in this post is limited, and eve...