Browsing by Subject "Data analysis"
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Item Open Access CONTEMPORARY JAPANESE ART AUCTION MARKET 2008-2017(2019) Feng, ShuochunThis project offers an introduction to the Japanese art auction market, analysis into insights for auction house specialization and segmentation, insights on the top 100 artists in terms of median hammer prices (unfiltered and filtered with at least ten works sold) and volume, the prominence of Avant-Garde artists in the Japanese art auction market from the years 2008 to 2017, and a new provenance model initiated through digital images in artist analysis. The goal of the project is to draw a general scope of view on Japanese art auction market through data visualization, as well as to offer rudimentary digital models for novel methodologies to approach art market research.
Japanese art auction houses have history back to the 1970s. In this project, six different auction houses were examined (Shinwa, Est-Ouest, Mainichi, SBI Art, The Mallet, and The Market). This range of auction houses reflects the segmentation in the Japanese art auction market, with Shinwa dominating the upper-end of sales, and Mainichi the lower-end. After analyzing the top 100 artists sorted by hammer price, median hammer price and volume and looking at sample works, it is concluded that the Japanese buyers favor relatively cheap art by Japanese paintings whose styles are reminiscent of more expensive Western artists. Among the top 100 by hammer price and median hammer price, many artists belong to the Avant-Garde movement, suggesting that the Japanese art auction market has a strong preference towards Avant-Garde artists.
It is generally considered that the art market is too complicated to be explained within a specific digital framework as there are too many social variables that are too difficult to recognize, yet it is still possible to address questions of market performances and characteristics, with sales prices as the primary information indicating values and relative scarcities. Also, by creating data matrices for pre-set art movements, historical periods and specific artists, the distinct roles that a movement or an artist played can be drawn into the big picture of the contemporary Japanese art market.
Item Open Access ENV 350S / PUBPOL 280S Seminar in Marine Conservation Leadership(2016) Stefanski, Stephanie; Smith, Martin DDuke PhD student Stephanie Stefanski recently taught a class focused on the process of designing, implementing, and analyzing the results from an economic valuation survey. The class was given as a module to inform the broader class themes of policy design and cost-benefit analysis in fisheries and marine resource management. The data file contains 1,526 observations of U.S. households who responded to an online Qualtrics survey in May 2012 about their familiarity with and willingness to pay to protect marine biodiversity in the Gulf of Mexico by paying additional taxes to fund an expansion of a marine sanctuary in the northern Gulf. There are 92 variables, which include socio-demographic characteristics of respondents, their answers to willingness to pay questions, and their answers to debriefing questions. Stephanie gave a presentation describing the context and motivation of the study and the main questions used in the survey. She then demonstrated to students the different data analysis commands and coding in Stata to visualize the data through histograms and frequency charts. These data visualizations informed the different types of regression analyses Stephanie taught the class. Finally, the students separated into small groups to discuss one of four policy implication discussion questions. The purpose of the exercise is to help students think critically about survey design and implementation, and how the results of surveys can be used to inform a variety of policies and to better understanding why people support environmental policy. The module successfully engaged students in learning about a published study and the data collection and analysis process it entailed. The class discussion fostered critical thinking about how to connect this type of data analysis and survey design to their own research and to addressing environmental challenges and policies beyond the scope of the study.Item Open Access Semantic Term “Blurring” and Stochastic “Barcoding” for Improved Unsupervised Text Classification(2018-04) Martorano, RobertThe abundance of text data being produced in the modern age makes it increasingly important to intuitively group, categorize, or classify text data by theme for efficient retrieval and search. Yet, the high dimensionality and imprecision of text data, or more generally language as a whole, prove to be challenging when attempting to perform unsupervised document clustering. In this thesis, we present two novel methods for improving unsupervised document clustering/classification by theme. The first is to improve document representations. We look to exploit “term neighborhoods” and “blur” semantic weight across neighboring terms. These neighborhoods are located in the semantic space afforded by “word embeddings.” The second method is for cluster revision, based on what we deem as “stochastic barcoding”, or “S- Barcode” patterns. Text data is inherently high dimensional, yet clustering typically takes place in a low dimensional representation space. Our method utilizes lower dimension clustering results as initial cluster configurations, and iteratively revises the configuration in the high dimensional space. We show with experimental results how both of the two methods improve the quality of document clustering. While this thesis elaborates on the two new conceptual contributions, a joint thesis by David Yan details the feature transformation and software architecture we developed for unsupervised document classification.