Sharing Research Data for Advancing Innovation and Scholarship

Dr. Matthew Zook from UK Department of Geography focuses on the value of openly sharing research data, especially in terms of how it contributes to scholarship, innovation, and the public good. The slide deck is available by clicking the Download button on the right. The video and photos of this segment are available for download by clicking the links listed under the additional files shown below

Big Data: Ethics, Resources, and Potential Collaboration

This presentation goes over 10 simple rules for responsible big data research

Crowd-Sourcing the Smart City: Using Big Geosocial Media Metrics in Urban Governance

Using Big Data to better understand urban questions is an exciting field with challenging methodological and theoretical problems. It is also, however, potentially troubling when Big Data (particularly derived from social media) is applied uncritically to urban governance via the ideas and practices of “smart cities”. This essay reviews both the historical depth of central ideas within smart city governance —particular the idea that enough data/information/knowledge can solve society problems—but also the ways that the most recent version differs. Namely, that the motivations and ideological underpinning behind the goal of urban betterment is largely driven by technology advocates and neoliberalism rather than the strong social justice themes associated with earlier applications of data to cities. Geosocial media data and metrics derived from them can provide useful insight and policy direction. But one must be ever mindful that metrics don’t simply measure; in the process of deciding what is important and possible to measure, these data are simultaneously defining what cities are

Improving Phonemic Awareness in ESL Pronunciation Using Shadowing During Tutorials: Implications for ESL Teachers

Although there are numerous reasons to improve pronunciation instruction, the teaching of phonologic structures in English has become less popular among k-12 classrooms. This study proposes that the use of a relatively new technique may positively improve ESL students\u27 pronunciation of American Standard English. This technique is known as shadowing. The data obtained was analyzed and evaluated in terms of phonological structures. The motivation to do this particular study came from previous research concerning word boundaries and phonological structures of consonants, in addition to my previous experience as an ESL tutor and instructor at SCSU. Students were making too many phonemic errors. This study will provide evidence for specific effects on phonemic awareness and also in regards to fluency and accuracy. To accomplish this, a shadowing methodology was used. The participants performed three types of audio-recorded speech samples both before and after their weekly tutorial sessions. Each would serve as a pre-test/post-test. First, spontaneous speech samples were used. Second, rehearsed speech samples were used. Third, read aloud activities were conducted to produce recorded speech samples. The recordings of speech samples were provided by four native speakers of English, two Caucasian males and two Caucasian females. This generated the authentic speech samples necessary for data analysis. The activities stemmed from a modified activity from the St. Cloud State ESL Department\u27s Tutorial packet. The samples were assessed by native speakers of English (speech sample raters) who listened to samples and scored each one based on a speech rubric provided by the researcher. The results of the data collected (scores from raters) were calculated and presented in the form of paired TTests. Common problems associated with pronunciation and whether the use of shadowing leads to an increased level of phonemic awareness were the target objectives for the elicited data. The students were divided into two groups. Student Group, A used a written transcript while making the shadowing attempts and Student Group B did not. The results indicated that most of the comparisons did not yield statistically significant results (gender and language yielded no significance). However, even though two of the mean scores for groups A and B ( comparing pre and post-test) yielded a difference, none of them were statistically significant as neither were equal or greater than the Alpha value of 0.05

Augmented Realities and Uneven Geographies: Exploring the Geolinguistic Contours of the Web

This paper analyzes the digital dimensions of places as represented by online, geocoded references to the economic, social, and political experiences of the city. These digital layers are invisible to the naked eye, but form a central component of the augmentations and mediations of place enabled by hundreds of millions of mobile computing devices and other digital technologies. The analysis highlights how these augmentations of place differ across space and language and highlights both the differences and some of the causal factors behind them. This is performed through a global study of all online content indexed within Google Maps, and more specific analyses of the linguistically and topically segregated layers of information over four selected places. The uneven linguistic geographies that this study reveals undoubtedly influence the many ways in which place is enacted and brought into being. The larger aim of this project is to use these initial mappings of the linguistic contours of the geoweb to push forward a broader debate about how augmented inclusions and exclusions, visibilities and invisibilities will shape the way that places become defined, imagined, and experienced

Viral Data

We are experiencing a historical moment characterized by unprecedented conditions of virality: a viral pandemic, the viral diffusion of misinformation and conspiracy theories, the viral momentum of ongoing Hong Kong protests, and the viral spread of #BlackLivesMatter demonstrations and related efforts to defund policing. These co-articulations of crises, traumas, and virality both implicate and are implicated by big data practices occurring in a present that is pervasively mediated by data materialities, deeply rooted dataist ideologies that entrench processes of datafication as granting objective access to truth and attendant practices of tracking, data analytics, algorithmic prediction, and data-driven targeting of individuals and communities. This collection of papers explores how data (and their absences) is figuring in the making of the discourses, lived realities, and systemic inequalities of the uneven impacts of the coronavirus pandemic

The Digital Knowledge Economy Index: Mapping Content Production

We propose the construction of a Digital Knowledge Economy Index, quantified by way of measuring content creation and participation through digital platforms, namely the code sharing platform GitHub, the crowdsourced encyclopaedia Wikipedia, and Internet domain registrations and estimating a fifth sub-index for the World Bank Knowledge Economy Index for year 2012. This approach complements conventional data sources such as national statistics and expert surveys and helps reflect the underlying digital content creation, capacities, and skills of the population. An index that combines traditional and novel data sources can provide a more revealing view of the status of the world’s digital knowledge economy and highlight where the (un)availability of digital resources may actually reinforce inequalities in the age of data

Attentional Social Media: Mapping the Spaces and Networks of the Fashion Industry

In this article we use big data methods to analyze the attention paid to the fashion industry on social media. The article argues that for the fashion industry, like many industries, the core product is a form of knowledge that is dependent on gaining and holding people’s attention. To understand this attentional economy, social media offers a unique window because it is increasingly a central space within which fashion knowledge is created and shared. Using long-term, geotagged big data from Twitter, we analyze the hitherto difficult-to-explore spaces and places of the global fashion industry. The article suggests that the data confirm the ideas that there are a series of global fashion capitals that are especially important to the industry and that attention paid to fashion is highly uneven and varied across industry functions, national origins, and companies. Evidence is presented that attention to fashion is a global phenomenon that does not always directly link to where fashion products are sold. Attention to fashion is both a market-making mechanism for the industry as well as an indicator of wider social and cultural processes of tastemaking and identity formation within which fashion is entwined. The article concludes by suggesting that such data offer geographers new ways of looking at and linking economic, social, and cultural spaces and geographies and that social media analysis can help bridge boundaries that divide geographers

New Economy Housing Markets: Fast and Furious - But Different?

This article explores the effects of metropolitan industrial structure on housing market outcomes. Housing prices in new economy metropolitan areas are found to be higher, peakier, and more volatile than in old economy markets. Homeownership rates are found to be lower in new economy metropolitan areas, while crowding is higher. Although the distribution of housing values, costs, and rents was more equal in new economy markets, the cause would seem to be differences in area income levels, with poorer metropolitan statistical areas having greater inequalities. Regression analysis is used to identify the contribution of traditional supply and demand factors, such as job growth, income, and residential construction, as well as new economy indicators, to housing market outcomes. Rather than being fundamentally different, new economy housing markets are found to be faster and more extreme versions of traditional housing markets