Understanding why users tag: A survey of tagging motivation literature and results from an empirical study

While recent progress has been achieved in understanding the structure and dynamics of social tagging systems, we know little about the underlying user motivations for tagging, and how they influence resulting folksonomies and tags. This paper addresses three issues related to this question. (1) What distinctions of user motivations are identified by previous research, and in what ways are the motivations of users amenable to quantitative analysis? (2) To what extent does tagging motivation vary across different social tagging systems? (3) How does variability in user motivation influence resulting tags and folksonomies? In this paper, we present measures to detect whether a tagger is primarily motivated by categorizing or describing resources, and apply these measures to datasets from seven different tagging systems. Our results show that (a) users’ motivation for tagging varies not only across, but also within tagging systems, and that (b) tag agreement among users who are motivated by categorizing resources is significantly lower than among users who are motivated by describing resources. Our findings are relevant for (1) the development of tag-based user interfaces, (2) the analysis of tag semantics and (3) the design of search algorithms for social tagging systems.     

Understanding why users tag: A survey of tagging motivation literature and results from an empirical study

While recent progress has been achieved in understanding the structure and dynamics of social tagging systems, we know little about the underlying user motivations for tagging, and how they influence resulting folksonomies and tags. This paper addresses three issues related to this question. (1) What distinctions of user motivations are identified by previous research, and in what ways are the motivations of users amenable to quantitative analysis? (2) To what extent does tagging motivation vary across different social tagging systems? (3) How does variability in user motivation influence resulting tags and folksonomies? In this paper, we present measures to detect whether a tagger is primarily motivated by categorizing or describing resources, and apply these measures to datasets from seven different tagging systems. Our results show that (a) users’ motivation for tagging varies not only across, but also within tagging systems, and that (b) tag agreement among users who are motivated by categorizing resources is significantly lower than among users who are motivated by describing resources. Our findings are relevant for (1) the development of tag-based user interfaces, (2) the analysis of tag semantics and (3) the design of search algorithms for social tagging systems.     

Expectations,learning and empirical macroeconomic models

The developments in the treatment of expectations in empirical macroeconomic models that have taken place over the last 30 years are surveyed. The main concern is to focus on the implications of expectation effects in the practical use of models, i.e. in forecasting and policy analysis, rather than to consider either the theoretical literature or the literature on econometric estimation and identification, both of which are already well surveyed. The general development in expectations models is discussed first. Then the literature on linear models is considered and the development of expectations effects to large nonlinear econometric models is examined.     

Password memorability and security: empirical results

Users rarely choose passwords that are both hard to guess and easy to remember. To determine how to help users choose good passwords, the authors performed a controlled trial of the effects of giving users different kinds of advice. Some of their results challenge the established wisdom.     

Comparison of multiobjective evolutionary algorithms: empirical results

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.     

Understanding corporate data models

Corporate data models are widely used to support data management within organisations. However, both IS professionals and business users find them difficult to understand. This paper describes a methodology for designing and representing corporate data models that uses explanation and visualisation mechanisms to improve understanding, and reports a case study of the use of the methodology in the development of a data warehouse. The methodology was shown to be effective in that a high quality corporate data model was designed and then understood and utilised by all the participants. The model was used as an active, hypertext interface to the first prototype of the data warehouse. The case study findings indicated that: scenarios are useful for eliciting information requirements and explaining abstract concepts in the model to business users; graphical icons and subject area partitions are effective means of visualising the model and lead to improved understanding of the model by business users; and design rationale is an effective means of explaining the evolution of concepts in the model for specialist data modellers.     

Comprehending object and process models: an empirical study

We report the results of an empirical study comparing user comprehension of object oriented (OO) and process oriented (PO) models. The fundamental difference is that while OO models tend to focus on structure, PO models tend to emphasize behaviour or processes. Proponents of the OO modeling approach argue that it lends itself naturally to the way humans think. However, evidence from research in cognitive psychology and human factors suggests that human problem solving is innately procedural. Given these conflicting viewpoints, we investigate empirically if OO models are in fact easier to understand than PO models. But, as suggested by the theory of cognitive fit, model comprehension may be influenced by task-specific characteristics. We therefore compare OO and PO models based on whether the comprehension activity involves: 1) only structural aspects, 2) only behavioral aspects, or 3) a combination of structural and behavioral aspects. We measure comprehension through subjects' responses to questions designed along these three dimensions. Results show that for most of the simple questions, no significant difference was observed insofar as model comprehension is concerned. For most of the complex questions, however, the PO model was found to be easier to understand than the OO model. In addition to describing the process and the outcomes of the experiments, we present the experimental method employed as a viable approach for conducting research into various phenomena related to the efficacy of alternative systems analysis and design methods. We also identify areas where future research is necessary, along with a recommendation of appropriate research methods for empirical examination     

Understanding consumer acceptance of mobile payment services: An empirical analysis

Mobile technology has become increasingly common in today’s everyday life. However, mobile payment is surprisingly not among the frequently used mobile services, although technologically advanced solutions exist. Apparently, there is still a lack of acceptance of mobile payment services among consumers. The conceptual model developed and tested in this research thus focuses on factors determining consumers’ acceptance of mobile payment services. The empirical results show particularly strong support for the effects of compatibility, individual mobility, and subjective norm. Our study offers several implications for managers in regards to marketing mobile payment solutions to increase consumers’ intention to use these services.     

Deliberate word access: an intuition,a roadmap and some preliminary empirical results

No doubt, words play a major role in language production, hence finding them is of vital importance, be it for writing or for speaking (spontaneous discourse production, simultaneous translation). Words are stored in a dictionary, and the general belief holds, the more entries the better. Yet, to be truly useful the resource should contain not only many entries and a lot of information concerning each one of them, but also adequate navigational means to reveal the stored information. Information access depends crucially on the organization of the data (words) and the access keys (meaning/form), two factors largely overlooked. We will present here some ideas of how an existing electronic dictionary could be enhanced to support a speaker/writer to find the word s/he is looking for. To this end we suggest to add to an existing electronic dictionary an index based on the notion of association, i.e. words co-occurring in a well balanced corpus, the latter being supposed to represent the average citizen’s knowledge of the world. Before describing our approach, we will briefly take a critical look at the work being done by colleagues working on automatic, spontaneous or deliberate language production,—that is, computer-generated language, simulation of the mental lexicon, or WordNet (WN),—to see how adequate they are with regard to our goal.     

Control theory models in world coffee : some empirical tests

A set of three control-theoretic models in differential games is empirically applied to test the role and behaviour of Brazil as a dominant supplier in the world coffee market. A comparative evaluation of the models across two sample periods 1945-61 and 1962-79 is performed along with tests for overall predictive power and stability. Since real-life applications of game theory models are few, it is surprising that these econometric models of differential games fit the empirical trend. More so, Brazil's role as a dominant supplier comes out in sharp focus through such features as cautious, adaptive behaviour in a fluctuating market and a sharp divergence from the strictly monopolistic strategy     

Understanding Web 2.0 service models: A knowledge-creating perspective

We examined Web 2.0 services that provide different levels of knowledge exploitation and developed a framework for classifying existing service models from a knowledge-creation perspective. More than 1000 Web 2.0 application sites were analyzed and classified. We termed the two types of service platforms: Experience-Socialization and Intelligence-Proliferation. These involved four types of service models that we termed as Exchanger, Aggregator, Collaborator, and Liberator. These models show the diversity of existing Web 2.0 applications and provide a framework for a better understanding of operating patterns and value propositions within the Web 2.0 paradigm.     

Reputation,framing strategies and user's choice of content on the Web: an empirical study

Current trends on the Internet indicate an increasing supply of content from anonymous users (e.g. blogs), which may become popular among website visitors. Motivated by these Internet trends, the present study explores the tradeoffs between the source's reputation and the way content is displayed or offered on the web page as well as the effects of both on the Internet user's choice of information services. The study builds upon behavioral economics and focuses on the interaction between background and local context effects on the individual's choice. In particular, the study investigates the tradeoffs between the source's reputation, representing the background context and the provision of enriched content (e.g. source bundled with a picture or a video) representing local context. The research involved a set of experiments based on hypothetical choice or matching tasks. The main findings indicate that there are significant interaction effects between reputation and enriched content, in the form of content related pictures, video and users' recommendations, which affect the user's choice of information services. Copyright © 2009 John Wiley & Sons, Ltd.     

Efficiency of mutation operators and selective mutation strategies: an empirical study

This paper investigates the mutation scores achieved by individual operators of the Mothra mutation system and their associated costs in order to determine the most efficient operators. The cost of mutation analysis includes both test set generation and equivalent mutant detection. The score and cost information is then used as a heuristic for choosing a subset of the operators for use in efficient selective mutation testing. Experiments were performed using a sample of 11 programs and a number of test sets for each program. The results show that the use of efficient operators can provide significant efficiency gains for selective mutation if the acceptable mutation score is not very close to one. When mutation scores very close to one are required, a randomly selected proportion of the mutants provides a more efficient strategy than a subset of efficient operators. Copyright © 1999 John Wiley & Sons, Ltd.     

An empirical evaluation of spatial regression models

Conventional statistical methods are often ineffective to evaluate spatial regression models. One reason is that spatial regression models usually have more parameters or smaller sample sizes than a simple model, so their degree of freedom is reduced. Thus, it is often unlikely to evaluate them based on traditional tests. Another reason, which is theoretically associated with statistical methods, is that statistical criteria are crucially dependent on such assumptions as normality, independence, and homogeneity. This may create problems because the assumptions are open for testing. In view of these problems, this paper proposes an alternative empirical evaluation method. To illustrate the idea, a few hedonic regression models for a house and land price data set are evaluated, including a simple, ordinary linear regression model and three spatial models. Their performance as to how well the price of the house and land can be predicted is examined. With a cross-validation technique, the prices at each sample point are predicted with a model estimated with the samples excluding the one being concerned. Then, empirical criteria are established whereby the predicted prices are compared with the real, observed prices. The proposed method provides an objective guidance for the selection of a suitable model specification for a data set. Moreover, the method is seen as an alternative way to test the significance of the spatial relationships being concerned in spatial regression models.     

Designing automation for human use: empirical studies and quantitative models

An emerging knowledge base of human performance research can provide guidelines for designing automation that can be used effectively by human operators of complex systems. Which functions should be automated and to what extent in a given system? A model for types and levels of automation that provides a framework and an objective basis for making such choices is described. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design when using the model. Four human performance areas are considered—mental workload, situation awareness, complacency and skill degradation. Secondary evaluative criteria include such factors as automation reliability, the risks of decision/action consequences and the ease of systems integration. In addition to this qualitative approach, quantitative models can inform design. Several computational and formal models of human interaction with automation that have been proposed by various researchers are reviewed. An important future research need is the integration of qualitative and quantitative approaches. Application of these models provides an objective basis for designing automation for effective human use.     

Designing automation for human use: empirical studies and quantitative models

An emerging knowledge base of human performance research can provide guidelines for designing automation that can be used effectively by human operators of complex systems. Which functions should be automated and to what extent in a given system? A model for types and levels of automation that provides a framework and an objective basis for making such choices is described. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design when using the model. Four human performance areas are considered--mental workload, situation awareness, complacency and skill degradation. Secondary evaluative criteria include such factors as automation reliability, the risks of decision/action consequences and the ease of systems integration. In addition to this qualitative approach, quantitative models can inform design. Several computational and formal models of human interaction with automation that have been proposed by various researchers are reviewed. An important future research need is the integration of qualitative and quantitative approaches. Application of these models provides an objective basis for designing automation for effective human use.     

New slug control strategies, tuning rules and experimental results

The challenge of handling intermittent flow with liquid slugs followed by gas pockets in multiphase flow lines becomes more important when the number of satellite fields increases. Oil, gas and water are transported from the wells in some km long flow lines along the seabed and up through a riser to the oil rig. Slugging may cause several problems for topside processing. This paper concerns suppression of slug flow by active use of the topside choke. Process measurements such as pressure and density are used in a PID controller. Slugging has been reduced significantly with such a system in operation offshore since April 2001. This paper contains results within simplified modelling of flow dynamics. New experimental results verify the dynamic model. A control scheme in operation offshore has been tested and a new control scheme independent of subsea measurements has been developed and tested in experiments.     

Design validation: comparing theoretical and empirical results ofdesign error modeling

To use simulation for design verification, designers need a confidence measure for a given set of simulation patterns, specifically for cases in which only a subset of the possible patterns is used. The authors derive a measure of design verification coverage based on the number of design errors detected in a theoretical analysis of a circuit. To verify the theoretical analysis, they simulate errors and compare the results