Online reviews are broadly believed to reflect consumers’ opinions towards the reviewed items. In this work, we postulate that online reviews for experience goods also reflect something very different, the reviewer’s emotions while experiencing the item. We study the case of films, which are made with the intent of evoking an emotional response. We postulate that the emotions that the viewer experienced while watching the movie are reflected in their online review, and can be reliably extracted from it. We aggregate these emotional experiences to create an emotional signature for the film—the emotions that it tends to evoke in viewers. We conduct a series of validations, each designed to offer evidence that the emotional signature indeed reflects the emotions that the film evokes in viewers. Our results demonstrate that experience goods’ online reviews can be utilized for extracting and understanding users’ emotional experience. Items’ induced emotions can be used in affective recommender systems and affective multimedia retrieval. In addition, users’ ability to easily see in advance the emotions that the item has induced in others, is relevant for research on the effect of expected emotions on decision-making.

Composite indicators (CIs) are common measurements and benchmarking tools used to measure multidimensional concepts such as well-being, education and more. Indicators and sub-indicators are selected and combined to reflect a measured phenomenon. Measurement iterations produce a series of time-oriented data, which stakeholders, as well as the general public, might be interested in interpreting. Visualization of a CI is highly recommended, in order to facilitate interpretation and enhance understanding of indicator components and their evolution over time. In recent years, a variety of CI visualizations have been published including various visualization techniques. Indeed, visualizing a CI is a complex and challenging issue, involving many design choices. However, there is a lack of guidelines and methodological approaches for CI visualization design. We suggest a framework that provides a systematic way of thinking of CI visualizations. The framework is intended for two uses: as a design tool when constructing a new CI visualization, and as an analytic tool for systematically describing, comparing and evaluating CI visualizations. The suggested framework is the outcome of both a top-down process, based on CI construction and information visualization literature, and a bottom-up process, in which 35 existing visualization applications of popular CIs were analyzed. We use Munzner’s visualization analysis and design framework (Munzner in Visualization analysis and design, CRC Press, Boca Raton, 2014) in an adaptive way, considering the specific challenges and characteristics of CI visualizations, in order to develop and discuss a systematic view of the data, tasks and methods for visualizing CIs. We demonstrate the use of the framework with a case study analyzing the popular OECD Better Life Index visualization tool.

A composite indicator (CI) is a measuring and benchmark tool used to capture multi-dimensional concepts, such as Information and Communication Technology (ICT) usage. Individual indicators are selected and combined to reflect a phenomena being measured. Visualization of a composite indicator is recommended as a tool to enable interested stakeholders, as well as the public audience, to better understand the indicator components and evolution overtime. However, existing CI visualizations introduce a variety of solutions and there is a lack in CI's visualization guidelines. Radial visualizations are popular among these solutions because of CI's inherent multi-dimensionality. Although in dispute, Radar-charts are often used for CI presentation. However, no empirical evidence on Radar's effectiveness and efficiency for common CI tasks is available. In this paper, we aim to fill this gap by reporting on a controlled experiment that compares the Radar chart technique with two other radial visualization methods: Flowercharts as used in the well-known OECD Betterlife index, and Circle-charts which could be adopted for this purpose. Examples of these charts in the current context are shown in Figure 1. We evaluated these charts, showing the same data with each of the mentioned techniques applying small multiple views for different dimensions of the data. We compared users' performance and preference empirically under a formal task-taxonomy. Results indicate that the Radar chart was the least effective and least liked, while performance of the two other options were mixed and dependent on the task. Results also showed strong preference of participants toward the Flower chart. Summarizing our results, we provide specific design guidelines for composite indicator visualization.

Composite Indicators (CIs), are a common measurement and benchmarking tool that are used to reflect and measure multidimensional concepts such as digital divides, individual's well-being and more. Measurement iterations produce a series of time-oriented data, which stakeholders as well as the general public might be interested to interpret. Visualization of a CI is highly recommended in order to ease interpretation, and many CI websites use radial solutions to visualize CIs. Yet it is unclear how to visualize the temporal dynamics in radial diagrams. Static solutions, mapping time to small multiples might be challenging due to screen space issues. Dynamic solutions are appealing, yet, there is no clear empirical evidence on benefits of dynamic time coding in radial diagrams. In this paper, we compare static vs. dynamic time mapping using two radial CI visualization methods. The popular Radar chart technique is compared to the innovative Flower chart as used in the well-known OECD Better Life index. We compare users' performance and preferences empirically under formal task taxonomy, adjusted to CI tasks. Results indicate that in general, static time encoding was more effective than dynamic encoding. Still, an in depth analysis showed that the dynamic approach is a feasible and sometimes even better solution for important CIs tasks, leveraged by the fact that users seem to like and enjoy it.

We present a work in progress on visualization of a popular Measurement and Benchmarking method, namely Composite Indicators (CIs). Composite indicators are increasingly recognized as an important tool in policy analysis and public communication and are often used to reflect performances of different units (e.g., countries, regions or organizations). Existing CI visualizations introduce a variety of solutions for the complex challenge of presenting multi-dimensional, time-oriented hierarchic data. Radial visualizations are popular among these solutions because of CI’s multi-dimensionality, although different coding is in use. In our work, we aim to shed light on radial presentations for multivariate temporal changes, hoping to produce relevant guidelines for CI visualizations. We introduce some radial design options with static and dynamic time coding, as we explore the design space. In future work, we plan to formally implement, and deploy selected designs.