Session:「Understanding through Visualization 1」

Improving Comprehension of Measurements Using Concrete Re-expression Strategies

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173608

論文アブストラクト: It can be difficult to understand physical measurements (e.g., 28 lb, 600 gallons) that appear in news stories, data reports, and other documents. We develop tools that automatically re-express unfamiliar measurements using the measurements of familiar objects. Our work makes three contributions: (1) we identify effectiveness criteria for objects used in concrete measurement re-expressions; (2) we operationalize these criteria in a scalable method for mining a large dataset of concrete familiar objects with their physical dimensions from Amazon and Wikipedia; and (3) we develop automated concrete re-expression tools that implement three common re-expression strategies (adding familiar context, reunitization and proportional analogy) as energy minimization algorithms. Crowdsourced evaluations of our tools indicate that people find news articles with re-expressions more helpful and re- expressions help them to better estimate new measurements.

日本語のまとめ:

ニュースなどでみられる測定値をわかりやすくするために,一般的なオブジェクトと測定値のデータベースを作成.再表現しなかった場合と比較して,データベースを使用した場合,エラー率は減少し,認知に有用だと答える人の数は18倍に増加した.

Uncertainty Displays Using Quantile Dotplots or CDFs Improve Transit Decision-Making

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173718

論文アブストラクト: Everyday predictive systems typically present point predictions, making it hard for people to account for uncertainty when making decisions. Evaluations of uncertainty displays for transit prediction have assessed people's ability to extract probabilities, but not the quality of their decisions. In a controlled, incentivized experiment, we had subjects decide when to catch a bus using displays with textual uncertainty, uncertainty visualizations, or no-uncertainty (control). Frequency-based visualizations previously shown to allow people to better extract probabilities (quantile dotplots) yielded better decisions. Decisions with quantile dotplots with 50 outcomes were(1) better on average, having expected payoffs 97% of optimal(95% CI: [95%,98%]), 5 percentage points more than control (95% CI: [2,8]); and (2) more consistent, having within-subject standard deviation of 3 percentage points (95% CI:[2,4]), 4 percentage points less than control (95% CI: [2,6]).Cumulative distribution function plots performed nearly as well, and both outperformed textual uncertainty, which was sensitive to the probability interval communicated. We discuss implications for real time transit predictions and possible generalization to other domains.

日本語のまとめ:

Dotplotsや累積分布関数といった不確実性の可視化手法を評価.被験者は不確実性の可視化図を用いてバスの到着時間を推測しました.50個のDotによって可視化した場合,到着予定時刻のみを可視化図と比較して,精度は5%高くなった.

Dream Lens: Exploration and Visualization of Large-Scale Generative Design Datasets

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173943

論文アブストラクト: This paper presents Dream Lens, an interactive visual analysis tool for exploring and visualizing large-scale generative design datasets. Unlike traditional computer aided design, where users create a single model, with generative design, users specify high-level goals and constraints, and the system automatically generates hundreds or thousands of candidates all meeting the design criteria. Once a large collection of design variations is created, the designer is left with the task of finding the design, or set of designs, which best meets their requirements. This is a complicated task which could require analyzing the structural characteristics and visual aesthetics of the designs. Two studies are conducted which demonstrate the usability and usefulness of the Dream Lens system, and a generatively designed dataset of 16,800 designs for a sample design problem is described and publicly released to encourage advancement in this area.

日本語のまとめ:

デザインのバリエーションの中から最良のデザインを探すという作業は複雑なため,デザイナーの負担が大きい.この研究では3Dデザインの集合から検索,フィルタリングをするシステムを提案した.

To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174122

論文アブストラクト: Laypeople are frequently exposed to unfamiliar numbers published by journalists, social media users, and algorithms. These figures can be difficult for readers to comprehend, especially when they are extreme in magnitude or contain unfamiliar units. Prior work has shown that adding "perspective sentences" that employ ratios, ranks, and unit changes to such measurements can improve people's ability to understand unfamiliar numbers (e.g., "695,000 square kilometers is about the size of Texas"). However, there are many ways to provide context for a measurement. In this paper we systematically test what factors influence the quality of perspective sentences through randomized experiments involving over 1,000 participants. We develop a statistical model for generating perspectives and test it against several alternatives, finding beneficial effects of perspectives on comprehension that persist for six weeks. We conclude by discussing future work in deploying and testing perspectives at scale.

日本語のまとめ:

ニュースなどでみられる測定値をわかりやすくするために,一般的なオブジェクトと測定値のデータベースを作成.再表現しなかった場合と比較して,データベースを使用した場合,エラー率は減少し,認知に有用だと答える人の数は18倍に増加した.