What people study when they study Twitter: classifying Twitter related academic papers

PURPOSE: Since its introduction in 2006, messages posted to the microblogging system Twitter have provided a rich dataset for researchers, leading to the publication of over a thousand academic papers. This paper aims to identify this published work and to classify it in order to understand Twitter based research. DESIGN/METHODOLOGY/APPROACH: Firstly the papers on Twitter were identified. Secondly, following a review of the literature, a classification of the dimensions of microblogging research was established. Thirdly, papers were qualitatively classified using open coded content analysis, based on the paper’s title and abstract, in order to analyze method, subject, and approach. FINDINGS: The majority of published work relating to Twitter concentrates on aspects of the messages sent and details of the users. A variety of methodological approaches are used across a range of identified domains. RESEARCH LIMITATIONS/IMPLICATIONS: This work reviewed the abstracts of all papers available via database search on the term “Twitter” and this has two major implications: 1) the full papers are not considered and so works may be misclassified if their abstract is not clear, 2) publications not indexed by the databases, such as book chapters, are not included. ORIGINALITY/VALUE: To date there has not been an overarching study to look at the methods and purpose of those using Twitter as a research subject. Our major contribution is to scope out papers published on Twitter until the close of 2011. The classification derived here will provide a framework within which researchers studying Twitter related topics will be able to position and ground their work

Multi-target out-of-sequence data association: tracking using graphical models

When performing data fusion, one often measures where targets were and then wishes to deduce where targets currently are. There has been recent research on the processing of such out-of-sequence data. This research has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships among the algorithms so that any approximations made are explicit. Results for a multi-sensor scenario involving out-of-sequence data association are used to illustrate the utility of this approach in a specific context.

Pianos for the people: the manufacture, marketing and sale of pianos as consumer durables, 1850-1914

During the second half of the nineteenth century, British society experienced a rise in real incomes and a change in its composition, with the expansion of the middle classes. These two factors led to a consumer revolution, with a growing, but still segmented, demand for household goods that could express status and aspiration. At the same time technological changes and new ways of marketing and selling goods made these goods more affordable. This paper analyzes these themes and the process of mediation that took place between producers, retailers, and consumers, by looking at the most culturally symbolic of nineteenth century consumer goods, the piano.