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.     

Content-based and collaborative techniques for tag recommendation: an empirical evaluation

The rapid growth of the so-called Web 2.0 has changed the surfers’ behavior. A new democratic vision emerged, in which users can actively contribute to the evolution of the Web by producing new content or enriching the existing one with user generated metadata. In this context the use of tags, keywords freely chosen by users for describing and organizing resources, spread as a model for browsing and retrieving web contents. The success of that collaborative model is justified by two factors: firstly, information is organized in a way that closely reflects the users’ mental model; secondly, the absence of a controlled vocabulary reduces the users’ learning curve and allows the use of evolving vocabularies. Since tags are handled in a purely syntactical way, annotations provided by users generate a very sparse and noisy tag space that limits the effectiveness for complex tasks. Consequently, tag recommenders, with their ability of providing users with the most suitable tags for the resources to be annotated, recently emerged as a way of speeding up the process of tag convergence. The contribution of this work is a tag recommender system implementing both a collaborative and a content-based recommendation technique. The former exploits the user and community tagging behavior for producing recommendations, while the latter exploits some heuristics to extract tags directly from the textual content of resources. Results of experiments carried out on a dataset gathered from Bibsonomy show that hybrid recommendation strategies can outperform single ones and the way of combining them matters for obtaining more accurate results.     

An empirical study of information contribution to online feedback systems: A motivation perspective

Online feedback systems (OFSs) are increasingly available on online shopping websites; they allow consumers to post their ratings and consumption reviews for products. We employed motivation theory and a goal attainment perspective to model a set of motivating and inhibiting factors that could influence a consumer's intention to contribute to an OFS. Our experiment, which involved 168 university students, showed that a consumer's intention to contribute product reviews is influenced by perceived satisfaction gained in helping other consumers, perceived satisfaction gained in influencing the merchant, perceived probability of enhancing self-image, and perceived executional costs. In addition, the presence of an economic rewarding mechanism was found to promote a contribution when a consumer's perceived probability of enhancing self-image was relatively high or when perceived cognitive cost was relatively low. Implications of our findings are discussed.     

Designing video games for the blind: results of an empirical study

Universal Access in the Information Society - Understanding non-functional software requirements and developing realizable operationalizations of them are critical to the success of any information...     

Minimum-weight spanning tree algorithms A survey and empirical study

The minimum-weight spanning tree problem is one of the most typical and well-known problems of combinatorial optimisation. Efficient solution techniques had been known for many years. However, in the last two decades asymptotically faster algorithms have been invented. Each new algorithm brought the time bound one step closer to linearity and finally Karger, Klein and Tarjan proposed the only known expected linear-time method. Modern algorithms make use of more advanced data structures and appear to be more complicated to implement. Most authors and practitioners refer to these but still use the classical ones, which are considerably simpler but asymptotically slower. The paper first presents a survey of the classical methods and the more recent algorithmic developments. Modern algorithms are then compared with the classical ones and their relative performance is evaluated through extensive empirical tests, using reasonably large-size problem instances. Randomly generated problem instances used in the tests range from small networks having 512 nodes and 1024 edges to quite large ones with 16 384 nodes and 524 288 edges. The purpose of the comparative study is to investigate the conjecture that modern algorithms are also easy to apply and have constants of proportionality small enough to make them competitive in practice with the older ones.Scope and purposeThe minimum-weight spanning tree (MST) problem is a well-known combinatorial optimisation problem concerned with finding a spanning tree of an undirected, connected graph, such that the sum of the weights of the selected edges is minimum. The importance of this problem derives from its direct applications in the design of computer, communication, transportation, power and piping networks; from its appearance as part of solution methods to other problems to which it applies less directly such as network reliability, clustering and classification problems and from its occurrence as a subproblem in the solution of other problems like the travelling salesman problem, the multi-terminal flow problem, the matching problem and the capacitated MST problem. Although efficient solution techniques capable of solving large instances had existed, there has been sustained effort over the last two decades to invent asymptotically faster algorithms. With each new algorithm found the time bound approached linearity. Finally, an expected linear-time method has been proposed. The purpose of this work is to survey the classical and modern solution techniques and empirically compare the performance of the existing methods.     

Ergonomics of electronic mail address systems: related literature review and survey of users

The paper reviews the cognitive ergonomics literature related to electronic mail (e-mail) address design. Based on this information, a survey of 160 users of current e-mail address system was conducted. The aim was to obtain information on likes, dislikes and difficulties associated with e-mail address and to obtain users' suggestions and input for improving the current e-mail address system. The survey results indicated that users want an improved e-mail address system with regard to shorter length, useful information and appropriate presentation of information.     

Ergonomics of electronic mail address systems: related literature review and survey of users

The paper reviews the cognitive ergonomics literature related to electronic mail (e-mail) address design. Based on this information, a survey of 160 users of current e-mail address system was conducted. The aim was to obtain information on likes, dislikes and difficulties associated with e-mail address and to obtain users' suggestions and input for improving the current e-mail address system. The survey results indicated that users want an improved e-mail address system with regard to shorter length, useful information and appropriate presentation of information.     

Impacts of courseware and student characteristics on learning achievement: results of an empirical study

Abstract Literature reviews revealed that not enough is known about specific software design and use features which contribute to learning effectiveness. Moreover, most research on these topics is carried out only in universities. Therefore, it was decided to conduct an empirical study with students of secondary schools, level two in Switzerland. Five classes and three pieces of courseware material were included in the study to investigate whether and how courseware and student characteristics have an impact upon the learning effectiveness.     

Configuring peer-to-peer software: an empirical study of how users react to the regulatory features of software

The emergence of new digital media has led to new sources and locations of power, and as a result, a heated debate on the regulability of cyberspace. The myth that cyberspace is by its nature free and uncontrollable has been challenged by Lessig's New Chicago School of Regulation that argues that code, or the architecture of information technologies, will be an important regulatory modality. This paper examines the relationship between regulation, information technologies and human behaviour, by examining what happens whenever individual human beings configure technology for use, in this case, file-sharing peer-to-peer applications. The evidence from the research suggests that Lessig's view does not capture all the nuances of practice involved in the use of peer-to-peer applications. The paper ends with proposals for future study of the actual practices of the users of this technology that will improve our understanding of the relationship between technology and regulation.     

Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model

As an innovation that revolutionizes application delivery based on cloud-computing, software-as-a-service (SaaS) has seen a tremendous growth during the last few years. However, its diffusion is not evenly distributed: some organizational users are open to SaaS but others are still hesitant despite the huge cost saving it may bring. The behavioral impacts of SaaS are far-reaching and the new socio-technical phenomenon deserves a close look. Based on the literature review, this study proposes a tripod model of SaaS Readiness that suggests that organizational users need to get prepared from technological, organizational and environmental aspects for the adoption of SaaS. The empirical results support that all three aspects are important for SaaS adoption yet their influences vary across psychological and overt outcome variables.     

The diversity of why: a meta-analytical study of usage motivation in enterprise social networks

In times of demographic change, skill shortage and disruptive innovations, organizational knowledge management and innovative capacity are the key to a company’s success. But how can knowledge be retained with fast staff turnover, global project-based work and parental leaves? Using enterprise social media to improve knowledge dissemination at work seems promising, when looking at the success of private social networking sites. In this article we combine ten different empirical studies which investigated different aspects of how user diversity influences the motivation to use social media at work. The emerging meta-study using the DerSimonian–Laird method (total sample size \(N=522\)) analyzes different aspects of user diversity and their correlation with eight motives for SNS usage: information, importance, contact, self-presentation, autonomy, social comparison, and power and control. We found that that the individual achievement motivation correlates positively with the motives importance, power, information and self-presentation. The need for autonomy correlates with openness to new experiences and the need for social comparison with gender and neuroticism. From our findings, we derive practical implications for designing a social networking site for work which fulfills the users’ needs and functions along their motivation.     

Pooling in convolutional neural networks for medical image analysis: a survey and an empirical study

Neural Computing and Applications - Convolutional neural networks (CNN) are widely used in computer vision and medical image analysis as the state-of-the-art technique. In CNN, pooling layers are...     

Explanations from knowledge-based systems and cooperative problem solving: an empirical study

Explanations are expected to play an important role when knowledge-based systems are used for cooperative problem solving. In this context both human and machine contribute to the procedures, constraints and strategies used in the problem-solving process. An increased need for explanations in this context is congruent with a cognitive-effort perspective and the Production Paradox observed with on-line help systems. This article describes an investigation of the role of explanations in cooperative problem solving. An experimental field study was performed with 41 users and an operational system for personal financial planning. The experiment showed a requirement for cooperative problem solving was associated with greater use of explanations. This effect was more marked with those users who had more fully explored the use of explanations during a preliminary stage of guided problem solving. The frequency of use of explanations in total was positively related to problem-solving performance. There was some evidence that the positive relationship between explanations and improved performance was more noticeable when problems requiring cooperation were undertaken.     

Municipal web sites accessibility and usability for blind users: preliminary results from a pilot study

Despite the existing regulations and standards at national and international level, web content is still difficult to use, if not completely unusable, for visually impaired people. This paper presents the evaluation results for three municipal web sites. A combined method, based on conformance review and expert review, was employed. Overall, the results reveal a low conformance to WCAG2 and many accessibility and usability problems. The content is not properly structured, and this reduces usability even for sighted user. The analysis of the evaluation data suggests that many accessibility barriers could be avoided by adopting a user-centered approach during web design.     

Teaching requirements elicitation interviews: an empirical study of learning from mistakes

Requirements Engineering - Interviews are the most widely used elicitation technique in requirements engineering (RE). However, conducting a requirements elicitation interview is challenging. The...     

Software complexity and software maintenance: A survey of empirical research

A number of empirical studies have pointed to a link between software complexity and software maintenance performance. The primary purpose of this paper is to document what is known about this relationship, and to suggest some possible future avenues of research. In particular, a survey of the empirical literature in this area shows two broad areas of study: complexity metrics and comprehension. Much of the complexity metrics research has focused on modularity and structure metrics. The articles surveyed are summarized as to major differences and similarities in a set of detailed tables. The text is used to highlight major findings and differences, and a concluding remarks section provides a series of recommendations for future research.     

Indicators for merge conflicts in the wild: survey and empirical study

While the creation of new branches and forks is easy and fast with modern version-control systems, merging is often time-consuming. Especially when dealing with many branches or forks, a prediction of merge costs based on lightweight indicators would be desirable to help developers recognize problematic merging scenarios before potential conflicts become too severe in the evolution of a complex software project. We analyze the predictive power of several indicators, such as the number, size or scattering degree of commits in each branch, derived either from the version-control system or directly from the source code. Based on a survey of 41 developers, we inferred 7 potential indicators to predict the number of merge conflicts. We tested corresponding hypotheses by studying 163 open-source projects, including 21,488 merge scenarios and comprising 49,449,773 lines of code. A notable (negative) result is that none of the 7 indicators suggested by the participants of the developer survey has a predictive power concerning the frequency of merge conflicts. We discuss this and other findings as well as perspectives thereof.     

In silico prediction methods of self-interacting proteins: an empirical and academic survey

In silico prediction of self-interacting proteins (SIPs) has become an important part of proteomics. There is an urgent need to develop effective and reliable prediction methods to overcome the disadvantage of high cost and labor intensive in traditional biological wet-lab experiments. The goal of our survey is to sum up a comprehensive overview of the recent literature with the computational SIPs prediction, to provide important references for actual work in the future. In this review, we first describe the data required for the task of DTIs prediction. Then, some interesting feature extraction methods and computational models are presented on this topic in a timely manner. Afterwards, an empirical comparison is performed to demonstrate the prediction performance of some classifiers under different feature extraction and encoding schemes. Overall, we conclude and highlight potential methods for further enhancement of SIPs prediction performance as well as related research directions.     

A survey of tagging techniques for music,speech and environmental sound

Sound tagging has been studied for years. Among all sound types, music, speech, and environmental sound are three hottest research areas. This survey aims to provide an overview about the state-of-the-art development in these areas. We discuss about the meaning of tagging in different sound areas at the beginning of the journey. Some examples of sound tagging applications are introduced in order to illustrate the significance of this research. Typical tagging techniques include manual, automatic, and semi-automatic approaches. After reviewing work in music, speech and environmental sound tagging, we compare them and state the research progress to date. Research gaps are identified for each research area and the common features and discriminations between three areas are discovered as well. Published datasets, tools used by researchers, and evaluation measures frequently applied in the analysis are listed. In the end, we summarise the worldwide distribution of countries dedicated to sound tagging research for years.