Abstract Title: Crowdsourcing – What motivates students to participate? Level: Bachelor thesis, 15 credits. Authors: Sara Örås & Tomas PetterssonSupervisor: Martin Amsteus Date: June 2013 Introduction: More and more companies realize the importance of using external resources to generate the best possible developmental outcomes for their particular business. The probability that all the smart people work for your company is not very big, therefore it is wise to use the public and take advantage knowledge, ideas and expertise of the public. Crowdsourcing is when a group of people is challenged to solve a problem for a company or to generate solutions and innovative ideas in exchange for compensation. A key issue is the question of what motivates individuals to participate in crowdsourcing. It is important to make people want to participate and it is very important to motivate the public in the right way. The purpose of the study is to investigate motivational factors in regard to crowdsourcing participation. Methodology: Method: A quantitative research approach has been chosen for this particular study as it aims to investigate and study the information in an objective perspective and thus creates an objective view of the reality. To examine the motivational factors, that are the most important to students when they participate in crowdsourcing, the study has been carried out in two steps, a focus group and a questionnaire-based survey. Since it is not reasonable to get in touch with the total population of university students, the population delimited to students at Linnaeus University in Växjö. Two selection methods are categorized as non-probability sample was used, convenience sampling and snowball sampling. Results: The three hypotheses of this study was rejected since the results of the analysis of the combined motivational factors did not demonstrate statistic significance. Statistical significance could however be demonstrated for individual motivational factors. Practical implications: The purpose of the study is to help companies while choosing incentives, and how to best motivate participants, in crowdsourcing projects. Key words: Crowdsourcing, Motivation / Sammanfattning Titel: Crowdsourcing – Vad motiverar studenter till att delta?Kurs: Kandidatuppsats, 15 högskolepoäng.Författare: Sara Örås & Tomas PetterssonHandledare: Martin Amsteus Datum: Juni 2013 Inledning: Idag inser många företag vikten av att använda sig utav externa resurser för att generera bästa möjliga utvecklingsresultat för just sitt företag. Då sannolikheten inte är så stor att alla smarta människor arbetar för just ditt företag är det väldigt klokt att använda sig av allmänheten för att utnyttja deras kunskap, idéer och kompetens. Crowdsourcing innebär att en grupp människor utmanas att lösa ett problem för ett företag för att generera lösningar och innovativa idéer i utbyte mot kompensation. En central fråga är vad som motiverar individer till att delta i crowdsourcing. För att få individer att vilja delta i crowdsourcing gäller det att motivera på rätt sätt. Syftet med uppsatsen är undersöka motivationsfaktorer i hänsyn till att delta i crowdsourcing. Metod: En kvantitativ forskningsansats har valts för just denna studie då det syftar till att undersöka och studera information på ett objektivt sätt och på så vis skapas en objektiv bild av verkligheten. För att undersöka vilka motivationsfaktorer som är viktigast för studenter när de skall delta i crowdsourcing har studien utförts i två steg, en fokusgrupp och en enkätbaserad surveyundersökning. Då det inte är rimligt att komma i kontakt med den totala populationen av universitetsstudenter har populationen avgränsats till studenter på Linnéuniversitet i Växjö. Två urvalsmetoder som tillhör kategorin icke-sannolikhetsurval har använts, bekvämlighetsurval samt snöbollsurval. Resultat: Studiens 3 hypoteser förkastas då resultatet av analysen av de sammanlagda motivationsfaktorerna ej kunde påvisa statistisk signifikans. Dock kunde statistisk signifikans påvisas på enskilda motivationsfaktorer. Praktiska implikationer: Studien syftar till att hjälpa företag vid val av incitament, samt hur de på bästa sätt kan motivera deltagare, i crowdsourcingprojekt. Nyckelord: Crowdsourcing, Motivation

Background: Successful crowdsourcing cannot be accomplished without a motivated community of participants. Hence, organisations need to use incentives that motivate the crowd to participate in crowdsourcing processes. Further, maintaining a working relationship between the organisation and the crowd throughout the duration of a project is a challenge with crowdsourcing. Thus, it creates difficulties in monitoring the quality of the outcome, which is the motivator for the organisation. However, previous studies have not covered the area of how the relationship between the organisation and the crowd influence their motivation. Purpose: Describe how motivation is influenced by the relationship between an organisation and the crowd in a crowdsourcing process.  Research questions: RQ1: How do an organisation and a crowd describe the relationship during the crowdsourcing process? RQ2: How do an organisation and a crowd describe their motivation during the crowdsourcing process? RQ3: How do the relationship between an organisation and a crowd influence motivation during the crowdsourcing process? Methodology: A single embedded case study, semi-structured interviews Conclusion: It is highly important that a company and a crowd have a good relationship in crowdsourcing, because it goes hand in hand with having a high motivation. It ought to be hard to state which term that influences the other, if it is the relationship that influences the motivation or if it is the motivation that influences the relationship. Thus, the result of this thesis explains that the relation between them is dynamic.

Cette thèse en trois essais s’appuie sur la recherche en cognition créatrice (« creative cognition ») (e.g., Finke, Ward, et Smith, 1992; Ward, 1998), avec pour objectif d’étudier la possibilité pour les entreprises d’engendrer plus efficacement de nouvelles idées créatives en s’appropriant les (nouveaux) outils et stratégies de marketing. Le premier essai résume les nombreuses études ayant trait à la créativité et propose un nouveau cadre, basé sur l’offre et la demande en matière de créativité dans le marketing, qui se veut un support pratique à la prise de décisions. Les essais 2 et 3 se penchent sur les études empiriques touchant à l’efficacité de deux types de modèles participatifs (« crowdsourcing »), dont le but est de solliciter un apport créatif de la part des consommateurs. Le second essai s’intéresse aux effets de la présentation d’un prototype de produit à un panel d’individus, en combinaison avec l’objectif du concept, sur les processus de génération d’idées et les résultats qui en découlent. Le troisième essai offre une perspective socio-cognitive des initiatives participatives, en examinant les effets conjoints du caractère novateur et de la notation d’idées soumises par d’autres communautés participatives sur la capacité subséquente d’une personne à générer de nouvelles idées. / Creativity is one of the cornerstones of marketing. Due to technological advances, companies have more tools and resources at their disposal for enhancing creativity. Drawing on creative cognition research, this dissertation aims to investigate how companies can maximize creativity with (new) marketing tools, techniques, and strategies. Essay 1 summarizes the vast body of research on creativity and proposes a novel framework that aims to guide managerial decision-making in practice by linking the demand and supply of creativity in marketing. Essay 2 and Essay 3 concern empirical studies on the effectiveness of two types of crowdsourcing practices that aim to solicit creative input from consumers. Essay 2 investigates the effects of the provision of a product prototype to individuals, in combination with the design goal, on idea generation processes and outcomes. Essay 3 proposes a socio-cognitive perspective on crowdsourcing initiatives by examining the joint effects of the novelty and ratings of ideas posted by others in crowdsourcing communities on a person’s subsequent idea generation performance.

Crowdsourcing involves releasing tasks on the internet for people with diverse backgrounds and skills to solve. Its adoption has come a long way, from scaling up problem-solving to becoming an environment for running complex experiments. Designing tasks to obtain reliable results is not straightforward as it requires many design choices that grow with the complexity of crowdsourcing projects, often demanding multiple trial-and-error iterations to properly configure. These inherent characteristics of crowdsourcing, the complexity of the design space, and heterogeneity of the crowd, set quality control as a major concern, making it an integral part of task design. Despite all the progress and guidelines for developing effective tasks, crowdsourcing still is addressed as an ``art'' rather than an exact science, in part due to the challenges related to task design but also because crowdsourcing allows more complex use cases nowadays, where the support available has not yet caught up with this progress. This leaves researchers and practitioners at the forefront to often rely on intuitions instead of informed decisions. Running controlled experiments in crowdsourcing platforms is a prominent example. Despite their importance, experiments in these platforms are not yet first-class citizens, making researchers resort to building custom features to compensate for the lack of support, where pitfalls in this process may be detrimental to the experimental outcome. In this thesis, therefore, our goal is to attend to the need of moving crowdsourcing from art to science from two perspectives that interplay with each other: providing guidance on task design through experimentation, and supporting the experimentation process itself. First, we select classification problems as a use case, given their importance and pervasive nature, and aim to bring awareness, empirical evidence, and guidance to previously unexplored task design choices to address performance concerns. And second, we also aim to make crowdsourcing accessible to researchers and practitioners from all backgrounds, reducing the requirement of in-depth knowledge of known biases in crowdsourcing platforms, experimental methods, as well as programming skills to overcome the limitations of crowdsourcing providers while running experiments. We start by proposing task design strategies to address workers' performance, quality and time, in crowdsourced classification tasks. Then we distill the challenges associated with running controlled crowdsourcing experiments, propose coping strategies to address these challenges, and introduce solutions to help researchers report their crowdsourcing experiments, moving crowdsourcing forward to standardized reporting.

"Human-Robot Interaction (HRI) is a rapidly expanding field of study that focuses on allowing non-roboticist users to naturally and effectively interact with robots. The importance of conducting extensive user studies has become a fundamental component of HRI research; however, due to the nature of robotics research, such studies often become expensive, time consuming, and limited to constrained demographics. This work presents the Robot Management System, a novel framework for bringing robotic experiments to the web. A detailed description of the open source system, an outline of new security measures, and a use case study of the RMS as a means of conducting user studies is presented. Using a series of navigation and manipulation tasks with a PR2 robot, three user study conditions are compared: users that are co-present with the robot, users that are recruited to the university lab but control the robot from a different room, and remote web-based users. The findings show little statistical differences between usability patterns across these groups, further supporting the use of web-based crowdsourcing techniques for certain types of HRI evaluations."

This study examines the motivations of participants in networked, large-scale content production and research a paradigm of distributed work magnified by the Internet. This has come to be called crowdsourcing. The approach taken in examining the crowdsourcing paradigm is of retrospection, with a study focused on observed examples and existing theories. Thirteen cases of existing crowdsourcing sites were selected for study, from a larger sample of 300. These cases were coded by their site properties and analyzed, identifying possible motivational mechanisms. Subsequent interviews with eight medium to heavy Internet users further explored these features, with an emphasis on ranking relative importance of various motivators. This study concludes with a series of recommendations on motivating crowds in such projects, emphasizing among others the importance of topical interest, ease of participation, and appeals to the individuals knowledge. In addition to base motivators, a number of support, or secondary, motivators are outlined.

Classic ways of gathering data on human behavior, such as laboratory based user studies, can be time-consuming, costly and are subject to limited participant pools. Crowdsourcing offers a reduction in operating costs and access to a diverse and large participant pool, however issues arise concerning low worker pay and questions about data quality. Gamification provides a motivation to participate, but also requires the development of specialized, research-question specific games that can be costly to produce. We provide another alternative that combines gamification and crowdsourcing in a smartphone-based system that emulates the popular Freemium model of micro-transactions to motivate voluntary participation through in-game rewards, using a robust framework to study multiple unrelated research questions within the same system. We deployed our prototype framework on the Android market and gathered data over a period of 5 weeks. We compared this data to that gathered from a gamified laboratory version and a non-gamified laboratory version, and found that players who use the in-game rewards were motivated to do experimental tasks. The data showed that there was no difference between the groups for performance on a motor task; however, performance on a cognitive task was worse for the crowdsourced Android group. We discuss the possible reasons for this and provide options for improving data collection and performance on tasks.

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Στις μέρες μας οι χρήστες εκτός από 'καταναλωτές' πληροφορίας στο διαδίκτυο είναι και 'παραγωγοί' και διαχειριστές της. Μια συνήθης πρακτική είναι η σήμανση του περιεχομένου που διαμοιράζονται με ετικέτες (tags) και η χρήση των ετικετών αυτών σε διαδικασίες αναζήτησης ή εύρεσης περιεχομένου με παρόμοια χαρακτηριστικά. Ένα από τα εργαλεία που ευρέως χρησιμοποιούνται στις διαδικασίες αυτές είναι οι ταξονομίες (taxonomies). Οι ταξονομίες είναι δενδρικές δομές που συνίστανται από κόμβους, καθένας από τους οποίους αντιπροσωπεύει μια κατηγορία-ένοια και συνδέεται με τα παιδιά και τον γονέα του με σχέσεις 'IS-A'. Δημιουργούνται κατά βάση χειρωνακτικά, από ειδικούς, ενώ η ανανέωση και επέκτασή τους είναι αρκετά χρονοβόρες ενέργειες. Στην εργασία αυτή ασχολούμαστε με την αυτόματη εξαγωγή ταξονομίας από είσοδο που προέρχεται από μια κοινότητα χρηστών. Θεωρούμε πως οι χρήστες μας είναι ικανοί να παρέχουν σχέσεις ετικετών που περιγράφουν καταστάσεις υπερκατηγορίας-υποκατηγορίας μεταξύ θεματικών κόμβων και προσπαθούμε να τις συγκεράσουμε ώστε να προκύψει μια ταξονομία. Η τελική ταξονομία είναι συμβατή με τα 'κβάντα' πληροφορίας που έχουμε στη διάθεσή μας, επιλύει αντικρουόμενες απόψεις χρηστών όσον αφορά την τελική της δομή και αποτυπώνει την ικανότητα της κοινότητας στη διακριτοποίηση εννοιών. Προτείνουμε έναν αλγόριθμο κατασκευής μιας ταξονομίας και θα αξιολογήσουμε την απόδοσή του, χρησιμοποιώντας τόσο συνθετικά, όσο και πραγματικά δεδομένα. Γίνεται επίσης προσαρμογή και μελέτη του συστήματος σε crowdsourcing περιβάλλοντα, περιβάλλοντα δηλαδή όπου ένας μεγάλος αριθμός από χρήστες χρησιμοποιείται για την περάτωση μικρών εργασιών που χαρακτηριστικό τους είναι η αδυναμία εκτέλεσης τους από υπολογιστικά συστήματα. / Taxonomies are a useful mechanism to organize, evaluate, and search web content. As such, many popular classes of web applications, utilize them. However, their manual generation and maintenance by experts is a timecostly procedure, often resulting in platform dependent and static vocabularies. We propose a new approach for constructing taxonomies. Our idea is based on the proven, increased human involvement and desire to annotate web content (e.g., in social media and product categorization applications). We define the required input from humans in the form of explicit structural, e.g., supertype-subtype relationships between concepts. In this way, we harvest, via common annotation practices, the collective wisdom of users with respect to the (categorization of) web content they share and access. We further define the principles upon which crowdsourced taxonomy construction algorithms should be based. We show that the resulting problem is NP-Hard. We provide heuristic algorithms that aggregate human input, resolving conflicting input, and produce taxonomies. We evaluate our algorithms with real world crowdsourcing experiments and on real world taxonomies.

Opioid users are an at-risk community. Risk of opioid overdose among substance users has increased tremendously in the last decade. Many factors, including adulterated drugs and hesitation in calling emergency response services, have led to many individuals not receiving the required harm reduction treatment, during an overdose incident. The problem is further compounded by the fact that many users are using alone in private residences and hence, no support mechanisms are available for them to assist them in case of an overdose situation. To circumvent this scenario, citizen training in Naloxone, an overdose harm reduction drug, has been promoted. However, there lies an essential communication gap between the citizens who have the training and the Naloxone kit and an active overdose event. Many at-risk communities may face the same challenge, especially if they are at risk of social isolation and voluntary/involuntary self-harm. Through our work, we wish to mobilize change in such at-risk communities, by studying the backend infrastructure of a crowdsourced emergency response system, called as a Peer Alerting Lifeline. The system would be responsible, for connecting peer responders, to an actual emergency event. Specifically, in the case of substance overdose, this would allow Naloxone kit holders to be informed of an overdose event in their vicinity and respond to the same. We aim to study the design infrastructure of such a system. / Graduate