Accurator: Nichesourcing for Cultural Heritage

With more and more cultural heritage data being published online, their usefulness in this open context depends on the quality and diversity of descriptive metadata for collection objects. In many cases, existing metadata is not adequate for a variety of retrieval and research tasks and more specific annotations are necessary. However, eliciting such annotations is a challenge since it often requires domain-specific knowledge. Where crowdsourcing can be successfully used for eliciting simple annotations, identifying people with the required expertise might prove troublesome for tasks requiring more complex or domain-specific knowledge. Nichesourcing addresses this problem, by tapping into the expert knowledge available in niche communities. This paper presents Accurator, a methodology for conducting nichesourcing campaigns for cultural heritage institutions, by addressing communities, organizing events and tailoring a web-based annotation tool to a domain of choice. The contribution of this paper is threefold: 1) a nichesourcing methodology, 2) an annotation tool for experts and 3) validation of the methodology and tool in three case studies. The three domains of the case studies are birds on art, bible prints and fashion images. We compare the quality and quantity of obtained annotations in the three case studies, showing that the nichesourcing methodology in combination with the image annotation tool can be used to collect high quality annotations in a variety of domains and annotation tasks. A user evaluation indicates the tool is suited and usable for domain specific annotation tasks

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

Target Type Identification for Entity-Bearing Queries

Identifying the target types of entity-bearing queries can help improve retrieval performance as well as the overall search experience. In this work, we address the problem of automatically detecting the target types of a query with respect to a type taxonomy. We propose a supervised learning approach with a rich variety of features. Using a purpose-built test collection, we show that our approach outperforms existing methods by a remarkable margin. This is an extended version of the article published with the same title in the Proceedings of SIGIR'17.Comment: Extended version of SIGIR'17 short paper, 5 page

Outsourcing labour to the cloud

Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area

Understanding the Detection of View Fraud in Video Content Portals

While substantial effort has been devoted to understand fraudulent activity in traditional online advertising (search and banner), more recent forms such as video ads have received little attention. The understanding and identification of fraudulent activity (i.e., fake views) in video ads for advertisers, is complicated as they rely exclusively on the detection mechanisms deployed by video hosting portals. In this context, the development of independent tools able to monitor and audit the fidelity of these systems are missing today and needed by both industry and regulators. In this paper we present a first set of tools to serve this purpose. Using our tools, we evaluate the performance of the audit systems of five major online video portals. Our results reveal that YouTube's detection system significantly outperforms all the others. Despite this, a systematic evaluation indicates that it may still be susceptible to simple attacks. Furthermore, we find that YouTube penalizes its videos' public and monetized view counters differently, the former being more aggressive. This means that views identified as fake and discounted from the public view counter are still monetized. We speculate that even though YouTube's policy puts in lots of effort to compensate users after an attack is discovered, this practice places the burden of the risk on the advertisers, who pay to get their ads displayed.Comment: To appear in WWW 2016, Montr\'eal, Qu\'ebec, Canada. Please cite the conference version of this pape

“Open Calls” Rather than “Fixed Assignments”: A Longitudinal Field Study of the Nature and Consequences of Internal Crowdsourcing

While the use of social IT-enabled “internal crowdsourcing” with employees in organizations has substantially increased in recent years (e.g., LEGO, IBM), internal crowdsourcing is not well understood from a theoretical point of view. In this research in progress, we build on the literature on new forms of organizing to improve our theoretical understanding of internal crowdsourcing, to consider whether it constitutes a theoretically distinct phenomenon, and to gain insights into its theoretical nature. The paper presents insights from an ongoing interpretivist field study of internal crowdsourcing at the multinational company BOSCH. Theorized as a form of organizing, we find that internal crowdsourcing is a very different form of organizing compared to work based on fixed assignments. Among the key dimensions of organizing, we identify internal crowdsourcing’s “open calls” model of work allocation as the key characteristic

What Makes a Successful Crowdfunding Campaign? A Case Study of Success Factors in Reward-Based Crowdfunding of Technology-Based Campaigns

Crowdfunding has become a popular method for founders of new ventures to acquire funding from individuals all around the world for varied projects. However, the factors influencing crowdfunding success are not well understood. This research aims to identify what makes a successful crowdfunding campaign by determining factors leading to success in crowdfunding campaigns, as well as explaining why and how those proposed factors influence crowdfunding success. The primary data for this qualitative case study were collected from three reward-based crowdfunding campaign founders in technology-based projects by using semi-structured interviews. Secondary data were gathered through direct observation from the case campaign websites. An inductive approach was used for this research. Thus, the analysis and theory building came during and after the data gathering. The research data were categorized and analyzed within and across the cases, and finally compared with existing research and theories. The research results indicated that there are at least seven factors influencing crowdfunding success, including product, pre-campaign community, team, presentation, awareness, preparation, and authenticity. Additionally, several explanations were provided to help understand why these factors were considered important. The main implications of this research concern product attributes and pre-campaign communities. The campaign founders considered products and various product attributes as one of the most important factors in crowdfunding success, suggesting further research of their dynamics in different campaign categories in reward-based crowdfunding. In addition, crowdfunding campaigns were found to benefit from pre-campaign communities by allowing crowds to be committed and involved in projects even before they enter a crowdfunding stage, thus increasing attention and the amount of potential funders. Finally, this research argues that more research is required to better understand the crowdfunding phenomenon by gathering data from new and diverse sources.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Crowdsourcing Emotions in Music Domain

An important source of intelligence for music emotion recognition today comes from user-provided community tags about songs or artists. Recent crowdsourcing approaches such as harvesting social tags, design of collaborative games and web services or the use of Mechanical Turk, are becoming popular in the literature. They provide a cheap, quick and efficient method, contrary to professional labeling of songs which is expensive and does not scale for creating large datasets. In this paper we discuss the viability of various crowdsourcing instruments providing examples from research works. We also share our own experience, illustrating the steps we followed using tags collected from Last.fm for the creation of two music mood datasets which are rendered public. While processing affect tags of Last.fm, we observed that they tend to be biased towards positive emotions; the resulting dataset thus contain more positive songs than negative ones