Dissertations / Theses on the topic 'Online data collection'

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2018
Cataloged from PDF version of thesis. Page 140 blank.
Includes bibliographical references (pages 134-139).
The strategies infants and young children use to understand the world around them provide unique insight into the structure of human cognition. However, developmental research is subject to heavy pragmatic constraints on recruiting large numbers of participants, bringing families back for repeat sessions, and working with special populations or diverse samples. These constraints limit the types of questions that can be addressed in the lab as well as the quality of evidence that can be obtained. In this dissertation, I present a new platform, "Lookit," that allows researchers to conduct developmental experiments online via asynchronous webcam-recorded sessions, with the aim of expanding the set of questions that we can effectively answer. I first present the results of a series of empirical studies conducted in the laboratory to assess difficulty faced by infants in integrating information across visual hemifields (Chapter 2), as an illustration of the creative workarounds in study design necessary to accommodate the difficulty of participant recruitment. The rest of this work concerns the development of the online platform, from designing the prototype (Chapter 3) and initial proof-of-concept studies (Chapter 4) to the demonstration of an interface for researchers to specify and manage their studies on a collaborative platform (Chapter 5). I show that we are able to reliably collect and code dependent measures including looking times, preferential looking, and verbal responses on Lookit; to work with more representative samples than in the lab; and to flexibly implement a wide variety of study designs of interest to developmental researchers.
by Kimberly M. Scott.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences

Thesis (M.S.)--University of North Carolina at Chapel Hill, 2007.
Title from electronic title page (viewed Dec. 18, 2007). "... in partial fulfillment of the requirements for the degree of Master of Science in the Department of Biomedical Engineering." Discipline: Biomedical Engineering; Department/School: Medicine.

1.1 Problem statement  This study looks to examine if and how patient/dentist contact can be reduced through remote diagnosis. The goal of the study is to formulate an understanding of what type of data needs to be collected and how to optimize the collection of that data (through digital platforms) to put together an odontological diagnosis that is as accurate as possible.  In other words, can medical diagnosis of the oral cavity be done correctly remotely? How is the process of remote odontological data collection optimized through platform design (interface and functionality)?  1.2 Methods  To collect remote data pertaining to the oral cavity and its health status a system is designed composed of three separate parts that interact. A database for the permanent storage of user data, a webpage for the collection of user data through user input and a backend system that acts as conveyer of information between the users and the database. Once the system is deployed user data is collected and interpreted, the quality of the data is then assessed by qualified dentists and the system modified based on the feedback from users and dentists. After the system has been modified it is redeployed, new data is collected, and its quality assessed and compared to the data previously collected. These modifications can be in the form of minor changes made to small parts of the system or major changes involving the entire system. Although this sort of feedback loop enhancement can be performed repeatedly during a long period of time, the goal is to complete two major iterations and a series of minor changes as feedback is obtained. User feedback will be received primarily through social media as the system does not allow users to express their opinions in any direct way. This is simplified by the fact that most users will be recruited through social media platforms.  1.3 Results  Although initially the concern was that users would have issues taking adequate images/videos of the oral cavity and its oral pathologies if present, this concern was quickly dismissed. The main issue users encountered were those related to navigation of the platform resulting in users submitting incomplete data. Once changes were applied to simplify navigation the results changed drastically, and majority of the data collected was complete. As data was collected it became clear that many different types of cases could be correctly diagnosed remotely, however, some cases inevitably will require a clinical examination to diagnose due to various factors such as the need for radiographs and/or dental probing. Nevertheless, the changes made to the platform over the iterations did help to optimise data collection significantly.

La popularité des médias sociaux en ligne (Online Social Media - OSM) est fortement liée à la qualité du contenu généré par l'utilisateur (User Generated Content - UGC) et la protection de la vie privée des utilisateurs. En se basant sur la définition de la qualité de l'information, comme son aptitude à être exploitée, la facilité d'utilisation des OSM soulève de nombreux problèmes en termes de la qualité de l'information ce qui impacte les performances des applications exploitant ces OSM. Ces problèmes sont causés par des individus mal intentionnés (nommés spammeurs) qui utilisent les OSM pour disséminer des fausses informations et/ou des informations indésirables telles que les contenus commerciaux illégaux. La propagation et la diffusion de telle information, dit spam, entraînent d'énormes problèmes affectant la qualité de services proposés par les OSM. La majorité des OSM (comme Facebook, Twitter, etc.) sont quotidiennement attaquées par un énorme nombre d'utilisateurs mal intentionnés. Cependant, les techniques de filtrage adoptées par les OSM se sont avérées inefficaces dans le traitement de ce type d'information bruitée, nécessitant plusieurs semaines ou voir plusieurs mois pour filtrer l'information spam. En effet, plusieurs défis doivent être surmontées pour réaliser une méthode de filtrage de l'information bruitée . Les défis majeurs sous-jacents à cette problématique peuvent être résumés par : (i) données de masse ; (ii) vie privée et sécurité ; (iii) hétérogénéité des structures dans les réseaux sociaux ; (iv) diversité des formats du UGC ; (v) subjectivité et objectivité. Notre travail s'inscrit dans le cadre de l'amélioration de la qualité des contenus en termes de messages partagés (contenu spam) et de profils des utilisateurs (spammeurs) sur les OSM en abordant en détail les défis susmentionnés. Comme le spam social est le problème le plus récurant qui apparaît sur les OSM, nous proposons deux approches génériques pour détecter et filtrer le contenu spam : i) La première approche consiste à détecter le contenu spam (par exemple, les tweets spam) dans un flux en temps réel. ii) La seconde approche est dédiée au traitement d'un grand volume des données relatives aux profils utilisateurs des spammeurs (par exemple, les comptes Twitter)
The popularity of OSM is mainly conditioned by the integrity and the quality of UGC as well as the protection of users' privacy. Based on the definition of information quality as fitness for use, the high usability and accessibility of OSM have exposed many information quality (IQ) problems which consequently decrease the performance of OSM dependent applications. Such problems are caused by ill-intentioned individuals who misuse OSM services to spread different kinds of noisy information, including fake information, illegal commercial content, drug sales, mal- ware downloads, and phishing links. The propagation and spreading of noisy information cause enormous drawbacks related to resources consumptions, decreasing quality of service of OSM-based applications, and spending human efforts. The majority of popular social networks (e.g., Facebook, Twitter, etc) over the Web 2.0 is daily attacked by an enormous number of ill-intentioned users. However, those popular social networks are ineffective in handling the noisy information, requiring several weeks or months to detect them. Moreover, different challenges stand in front of building a complete OSM-based noisy information filtering methods that can overcome the shortcomings of OSM information filters. These challenges are summarized in: (i) big data; (ii) privacy and security; (iii) structure heterogeneity; (iv) UGC format diversity; (v) subjectivity and objectivity; (vi) and service limitations In this thesis, we focus on increasing the quality of social UGC that are published and publicly accessible in forms of posts and profiles over OSNs through addressing in-depth the stated serious challenges. As the social spam is the most common IQ problem appearing over the OSM, we introduce a design of two generic approaches for detecting and filtering out the spam content. The first approach is for detecting the spam posts (e.g., spam tweets) in a real-time stream, while the other approach is dedicated for handling a big data collection of social profiles (e.g., Twitter accounts)

As part of the ReadNPlay for a Bright Future initiative, an online survey was conducted to determine the preferences of parents and caregivers in regards to receiving health information and support and to identify opportunities to improve existing support groups in Northeast Tennessee. An anonymous online survey with ten closed-ended questions was designed on Survey Monkey and posted on social media sites of the ReadNPlay project, BABE Regional Breastfeeding Coalition, and local mothers’ support groups. After a two-week period, during which a reminder of the survey was posted, the results of the survey were summarized using Survey Monkey and Excel. A total of 39 surveys were collected. Of the 39 participants, all identified themselves as either a mother (97.44%) or other female caregiver (2.56%). Sixty three percent of mothers and caregivers wanted to receive support or health information through face-to-face support group meetings compared to 78.95% who wanted to receive the same information through social media and 68.42% who wanted to receive information via email. Less popular options for receiving health information and support include community events (60.53%), classes (44.74%), text messages (36.84%), childcare centers/schools (34.21%), handouts from healthcare providers (28.95%), and snail mail (21.05%). Forty six percent of respondents have attended support group meetings several times, 41.03% have never attended a support group meeting, and 15.38% have only attended a support group meeting once. Mothers and other caregivers identified the greatest barriers to participation in a support group as inconvenient timing (47.22%), lack of time (50%), inconvenient locations (47.22%), and lack of information about time and location (25%). Respondents were interested in receiving the following health and parenting information: learning/development (83.78%) breastfeeding (75.68%), active play (75.68%), behavior (72.97%), nutrition (64.86%), safety (45.95%), and prevention (40.54%). Mothers and other caregivers were interested in receiving the following types of support when they attend group meetings: socialization with other parents (81.58%), activities sponsored by community organization (78.95%), information about community resources (65.79%), parenting tips (63.16%), health information (44.74%), and food and supplies (34.21%).Additionally, when respondents were asked to identify preferred locations for support group meetings, the most popular option was a kid-friendly location (97.37%) followed by a community center (57.89%). The results obtained above are being used to improve existing support groups by providing parents and caregivers with child-friendly environments in which to socialize and receive a variety of parenting information, including information on learning and development.

This study examines how consumers reason and their opinions about personal data collection online. Its focus is to investigate whether consumers consider online data collection as an issue with moral implications, and if these are unethical. This focus is partly motivated by the contradiction between consumers’ stated opinions and actual behavior, which differ. To meet its purpose, the study poses the research question How is personal data collection and its prevalence online perceived and motivated by consumers?. The theoretical framework consists of the Issue-Contingent Model of Ethical Decision-Making by Jones (1991), thus putting the model to use in a new context. Collection of data for the study was done by conducting focus groups, since Jones’ model places ethical decision- making in a social context. The results of the study showed that consumers acknowledge both positive and negative aspects of online data collection, but the majority of them do not consider this data collection to be unethical. This result confirms partly the behaviour that consumers already display, but does not explain why their stated opinions do not match this. Thus, this study can be seen as an initial attempt at clarifying consumer reasoning on personal data collection online, with potential for future studies to further investigate and understand consumer online behaviour.
Denna uppsats undersöker hur konsumenter resonerar och tänker kring insamling av personlig data på Internet. Fokus är att utreda ifall konsumenter anser att denna insamling har konsekvenser, och ifall dessa anses vara oetiska. Detta fokus baseras delvis på resultat som visar på skillnader i vad konsumenter uttrycker för åsikter kring detta ämne, och deras faktiska beteende på Internet. Undersökningen utgår ifrån forskningsfrågan som lyder Hur uppfattar och motiverar konsumenter insamling av personlig data på Internet? Studiens teoretiska ramverk består av modellen An Issue-Contingent model of Ethical Decision- Making som är utvecklad av Jones (1991), och modellen används därmed i en ny kontext. Studiens data samlades in genom fokusgrupper. Detta val baserades på Jones (1991) modell, som menar att etiskt beslutsfattande alltid sker i en social kontext. De resultat som kommit fram visar att konsumenter ser både positiva och negativa aspekter och konsekvenser av att ha sin personliga data insamlad, däremot utan att anse att insamlingen i sig är oetisk. Detta bekräftar delvis tidigare resultat, men förklarar inte varför de åsikter konsumenter uttrycker kring ämnet inte stämmer överens med hur de sedan faktiskt beter sig. Därmed kan den här uppsatsen ses som ett första försök att klargöra hur konsumenter resonerar kring insamling av personlig data på Internet. Det har bedömts finnas mycket potential för framtida studier inom samma område, för att fortsatt undersöka och förstå konsumenters beteende på Internet.

Background: Pain is a common consequence of Spinal Cord Injury (SCI). While research into pain in SCI is vast, examining musculoskeletal pain (MSKP) and low back pain (LBP) are limited. This thesis aims to investigate these categories of pain in incomplete SCI (iSCI). The experience of pain is known to affect quality of life (QoL) and function. The impact of the experience of pain, particularly of LBP, on both the QoL and function are examined in this research. While research in similar fields is predominantly conducted in single nation populations this research is set out to study three different nations. Method: The following were part of this study: • A systematic literature review on the prevalence on chronic back pain (BP), LBP and MSKP in SCI. • A translation, and preliminary validation, into Greek of the Spinal Cord Independence Measure (SCIM version III). • A cross-national survey conducted in the USA, UK and Greece. Questionnaires included the short-form McGill Pain questionnaire (SF-MPQ), EQ-5D and the SCIM III. They were collected either online or via post and 219 questionnaires were analysed. Results: The papers included in the systematic literature review were considerably heterogeneous not allowing meta-analysis to be made. 95% confidence intervals (CI) for the total number of participants in the studies were used. Among people with pain the prevalence of chronic MSKP (CMSKP) was 49% (95%CI 44%, 55%), of chronic BP (CBP) was 47% (95%CI 43%, 50%) and chronic LBP (CLBP) was 49% (95%CI 44%, 55%). GR-SCIM III maintains its unidimensionality and has acceptable internal consistency (α=0.78). Concurrent/criterion validity for the two cross-examined subscales were strong for “self-care” (ρ=-0.78) and moderate for “mobility” (ρ=-0.58). Unidimensionality was also confirmed for the English version of SCIM III, which had accepted internal consistency (α=0.79) and strong concurrent/criterion validity for “self-care” (ρ=-0.75) and moderate for “mobility” (ρ=-0.45). The survey results showed that the prevalence of current LBP is 67.9% (95%CI 61%, 73%) and of MSKP is 38.8% (95%CI 32%, 45%). LBP was of moderate intensity and most commonly described as “aching”. People who report pain, LBP or MSKP reported worse QoL. The impact of LBP on QoL was greater than that of pain in general or MSKP. The increased intensity of LBP correlated with worse function. Among the three participating countries, people from the UK had the worst experience of pain and LBP, classified themselves with the worst health status and reported the worst functional independence. Conclusion: This study offers the first systematic review on CLBP, CBP and CMSKP in SCI. It is unique in using SCIM III by self-report and into Greek. The results show that LBP is highly present in iSCI affecting both QoL and function. Both the GR-SCIM III and the SCIM III are reliable for use, however studies are needed to examine further their psychometric properties. The findings of the study fit with features of the currently used patients’ rehabilitation models.

From the days of Antonio Meucci and Alexander Graham Bell when the telephone was invented, people have been looking for ways to communicate with each other through the use of technology. With the introduction of the Internet new possibilities were created to communicate with other persons around the world. As more and more individuals got access to the Internet more and more data got sent through the network. As with any platform where number of individuals keeps growing, business is to be made. Different companies offer different types of services, and many of these companies are niched in services where people in some way interact with each other. Social communities are some of the largest websites that are used and on these websites a lot of data is being shared. Pictures, life stories and interests are shared and this data is something that advertisement companies pay money to obtain. We can see this since a large part of revenues from social communities come from ad companies. Since these websites save data about individuals one could collect this data to sum up how an individual act online. In this thesis, we wanted to see if there was any interest in collecting this type of data to develop a business model where the data of individuals would be sold to a third party, and how individuals feel about this type data collection. To get an understanding of what type of data that can be collected, different companies that gather data were looked into. To get an understanding if this business model is something wanted recruiters of different IT companies were contacted for interviews. Focus groups and surveys were used to see how individuals close to their college graduation feel about data collection and the business model that is under construction. From the data collected, we saw that recruiters were not interested in a business model that gathered personal data, but rather professional data such as education, projects and other job related facts that can prove what the job applicant have done. And from the public we got the response that data collection of this sort is not something that is desirable. With the data collected we saw that our business model did not fit our targeted audience, but rather that a modified business model aimed on professional data rather than social data is something that could be developed.
Ända sedan den dagen telefonen skapades av Antonio Meucci och Alexander Graham Bell har människan letat efter nya sätt att kommunicera med varandra via teknologin som finns idag. Internet har introducerade nya sätt att dela olika typer av data världen över. Varje dag får fler och fler människor tillgång till internet det betyder då också att mer data skickas via nätet. Som med alla plattform där antalet individer växer skapas då nya affärsmodeller. Olika företag erbjuder olika typer av tjänster och många av dessa företag fördjupar sig inom kommunikationssektorn så att människor kan integrera med varandra. Socialmedia är bland de populäraste webbsidorna idag och här kan användarna dela data och information med varandra. Dessa data är viktiga för annonseringsföretagen då de vill rikta rätt reklam till användarna. Detta ser vi nu eftersom sociala mediernas största inkomstkälla kommer ifrån säljandet av data till annonsering bolagen. Man skulle kunna ta all data som dessa företag har sparat på sina användare för att sammanställa hur de använder tjänsten. I vår rapport ville vi se om det dann något intresse för att samla in denna typ av data för att utveckla vår affärsmodell där individens data och information säljes till en tredje part. Vi ville även undersöka hur användaren känner när det gäller datasamling på internet. För att få en uppfattning på vad för data som kan samlas in på internet har vi undersökt två företag för att se vad för data de tar. När det gäller vår affärsmodell har vi kontaktat och intervjuat rekryterare från olika företag för att se om vår affärsmodell är något som de behöver. Focused Groups och enkäter skickades ut till studenter som nästan har sin examen för att höra vad de har för åsikt är gällande datainsamling och vår affärsmodell. Vår undersökning visade att datainsamling inte var eftertraktad, men de ville däremot samla kompetens information istället. Information så som utbildning, projekt och arbetskarriär. Enkäten och Focused Groups visade även där att personlig datainsamling inte var något som de ville ha. Med de data vi fått under vår undersökning tydde det på att vår affärside inte var riktad mot rätt målgrupp, men en justering av vår affärsmodell i form av datainsamling av kompetens information var något de ville ha.

Data collection and online personalization has become essential part of modern marketing, and thus, embedded into consumer’s everyday life. This has emerged a lot of negative attention in the media and privacy concerns among consumers – however, their attitudes towards privacy seems to be controversial with lack of privacy enhancing behavior. The purpose of this study was to find out what is consumers take on online personalization, data collection and GDPR. In order to the tackle the causing reasons of such perceptions, focus group discussions were performed. The emerging thoughts were analyzed with the concepts of privacy paradox and information asymmetry – how structural imbalance between the advertisement network, companies and consumers impacted to their thinking about personalization and which factors caused the unwillingness to enhance one’s privacy, despite the attitudes that would predict different behavior. The results showed, that many respondents do not mind personalization if they perceive it relevant. However, the intrusive nature of its practices made the participants, directly or indirectly, reluctant towards it, as it was highlighted that it is not personalization per se that made the respondents uncomfortable, but how it was done. Due to the advertisement networks’ opaque nature, the participants founded challenging to comprehend how personalization was performed. Thus, conspiracy theories about surveillance, such as tapping via smartphone, were broad up to explain companies’ ability to know and target them so well. The main channel for companies to inform consumers about their privacy policy is terms and conditions. However, due to several reasons, the decision making for one’s privacy face many hinders, that may influence in how consumers perceive their privacy and how their personal data is collected and used. A controversiality between GDPR’s, companies’ and consumers’ view on privacy self-management is evident, as the regulation and companies rely too much on consumer’s own responsibility.

Although the primary role of the computer has been in processing and analysis of survey data, it has increasingly been used in data collection. Computer surveys are not exempt from a common problem: some refuse to participate. Many researchers and practitioners indicate the refusal problem is less for computer surveys, perhaps due to the novelty of the method. What has not been investigated is the refusal problem when on-line surveys are no longer novel. This research study examines the use of one form of computer-assisted data collection, the electronic or on-line survey, as an organizational research tool. The study utilized historical response data and administered an on-line survey to individuals known to be cooperative or uncooperative in other on-line surveys. It investigated nonresponse bias and response effects of typical responders, periodic participants, and typical refusers within a sample of corporate employees in a computer-interactive interviewing environment utilizing on-line surveys. The items measured included: participation, respondent characteristics, response speed, interview length, perceived versus actual interview length, quantity of data, item nonresponse, item response bias, consistency of response, extremity of response, and early and late response. It also evaluated factors reported as important when deciding to participate, preferred data collection method, and preferred time of display. Past participation, attitudes toward on-line organizational surveys, response burden, and response error were assessed. The overall completion rate of 55.7% was achieved in this study. All effort was made to encourage cooperation of all groups, including an invitation to participate, token, on-line pre-notification, 800 number support, two on-line reminders, support of temporary exit, and a paper follow-up survey. A significant difference in the participation of the three groups was found. Only three demographic variables were found to be significant. No significant differences were found in speed of response, interview length, quantity, item nonresponse, item response bias, consistency, and extremity. Significant differences were found in the perceived and actual times to complete the survey.

With the increase in the use of online professional development resources, especially for rural educators, this study evaluated the effects of online training modules on in-service teachers' ability to collect and use instructional progress monitoring data to make instructional decisions for students with significant disability (i.e., moderate to severe intellectual disability, autism). In this randomized control study, 29 teachers across three states participated in online data collection or data collection plus data-based decision making training. In addition, the generalization of teachers' ability to use data-based decisions with their own student outcome data were measured. Results indicated that while the modules did support teachers' acquisition of new information, they were not sufficient to carry over to applied use on their own students' data. Further discussion on the use of module-based professional development will be presented as well as how teachers in rural areas can access this information.

Digitala spel har blivit ett allt vanligare sätt för underhållning, där industrin har sett en stor ökning av användare, vilket har stor sannolikhet att fortsätta även i framtiden. Dessa spel har ökat i komplexitet i takt med den teknologiska utvecklingen från 90-talet tills idag, där Internet har haft stor påverkan och introducerat nya möjligheter. En utav dessa möjligheter är insamlingen av olika datatyper med olika syften och olika användningsområden inom ett spelutvecklingsföretag. Industrin har lockat mycket forskning angående processer och metoder som berör skapandet av dessa komplexa produkter, där förarbetet och själva skapandet av digitala spel tar upp majoriteten av forskning i jämförelse med vidareutvecklingen av dessa digitala spel efter lansering. Syftet med denna rapport är därmed att bidra med kunskap till det mindre utforskade området kring utvecklingsprocessen efter lansering av online multiplayerspel, samt undersökning och insamling av data och dess integrering i vidareutvecklingsprocessen. Första viktiga delen av rapporten är ett teoriavsnitt, skapad genom en litteraturstudie där denna bestod av att identifiera och hitta vetenskapliga artiklar med kunskap kring ämnet, där dessa var viktiga för att skapa en teoretisk grund för denna studie. Detta gjordes huvudsakligen genom vetenskapliga databaser och söktjänster, med hjälp av nyckelord relaterade till viktiga teorier. Den andra viktiga delen är empiriska studier i form av semistrukturerade intervjuer utifrån en intervjuguide med respondenter från olika spelutvecklingsföretag. Företagen som respondenterna jobbade för var Ghost Ship Games, Jagex, samt Bohemia Interactive. Dessa intervjuer har sedan analyserats och viktiga teman har identifierats utifrån respondenternas svar. Respondenterna har nämnt olika datatyper som kan täcka olika delar av företaget, men när det gäller vidareutveckling av spel har tre typer nämnts att ha störst påverkan. Dessa typer var datapunkter över hur spelet används av individer, kvalitetsdata av spelets prestanda samt feedback från användare. Metoderna för att samla in de förenämnda datatyperna består framförallt av enkäter som alla respondenter har nämnt att respektive företag använder för att samla in feedback, rapportering av bugs eller förslag på förbättringsområden. Utöver detta samlas även mer övergripande information genom digitala verktyg eller spelklienten för respektive spel. Där dessa verktyg är skapade inom företaget eller hanteras genom ett separat företag. Ghost Ship Games har nämnt en egen idealbild över hur spelet ska vara balanserat som företaget strävar efter, vilket tas i åtanke vid beslut som tas av utvecklarna som täcker respektive problem. Inom Jagex är det hela team som bestämmer tillsammans angående förändringar eller tillägg i spelet. En intressant aspekt var att för Jagex så är användarna en del av beslutsfattandet genom opinionsundersökningar. Beslutsfattandet inom Bohemia Interactive nämndes att ske huvudsakligen genom avdelningen för kvalitetssäkring, där dessa filtrerar insamlad information och sedan delegerar identifierade problem till rätt utvecklare inom företaget. Vidareutvecklingen inom företagen gjordes framförallt genom balansering med hjälp av spelmotorn för respektive spel. Ghost Ship Games fokuserar även på vidareutveckling av befintliga funktioner, system och verktyg, genom att omarbeta några av föregående delar. Inom Bohemia Interactive angående Arma 3 användes till exempel hotfixes eller helt nytt spelinnehåll genom DLC, liknande sker även inom Jagex i form av hotpatches. Övergripande så är vidareutvecklingsprocessen lik mellan företagen, genom de olika steg som har identifierats i denna rapport. Dessa kan beskrivas som en iterativ process där företag identifierar problem eller förslag för vidareutveckling, samlar in eller undersöker befintlig data för att bekräfta problem eller stödja förslag, implementerar lösning eller förslag, samt samlar in feedback och agerar utifrån feedback.
Digital games have become an increasingly common means of entertainment where the industry has seen a huge increase in users, something that is likely to continue in the future. These games have increased in complexity in line with technological developments from the 1990s to the present day, where the Internet has had a major impact and introduced new possibilities. One of these opportunities is the collection of different types of data with different purposes and different uses within a game development company. The industry has thus attracted a lot of research regarding processes and methods involved in the creation of these complex products, where the pre-processing and actual creation of digital games is in the vast majority of studies compared to the further development of these digital games after launch. The aim of this paper is therefore to contribute knowledge to the less explored area of the post-launch development process of online multiplayer games, as well as the investigation of data collection and its integration into the further development process. The first important part of the report is a theory section, created through literature review where this consisted of identifying and finding scientific articles with knowledge on the topic, where these were important to create a theoretical basis for this study. This was mainly done through scientific databases and search services, using keywords related to important theories. The second important part is empirical studies in the form of semi-structured interviews based on an interview guide with respondents from different game development companies. The companies the respondents worked for were Ghost Ship Games, Jagex, and Bohemia Interactive. These interviews were then analysed and important themes were identified based on the respondents’ answers. Respondents mentioned different types of data that could cover different parts of the company, but when it comes to further game development, three types were mentioned to have the most impact. These types were data points on how the game is used by individuals, quality data of the game's performance, and feedback from users. The methods for collecting the aforementioned data types consist mainly of surveys, which all respondents mentioned that the respective companies use to collect feedback, report bugs or suggest areas for improvement. In addition, more general information is also collected through digital tools or the game client for the respective game. Where these tools are created within the company or managed by a separate company. Ghost Ship Games has an ideal image of how the game should be balanced that the company strives for, which is taken into account when decisions are made by the developers themselves that cover the respective issues. Within Jagex, the whole team decides together on changes or additions to the game. An interesting aspect is that within Jagex, users are a part of the decision making process through opinion polls. Decision-making within Bohemia Interactive is mainly done through the Quality Assurance department, where they filter collected information and then delegate identified problems to the appropriate developers within the company. Further development within the companies is mainly done through balancing using the game engine for each game. Ghost Ship Games may also focus on further development of existing features, systems and tools, by reworking some of the previously mentioned elements. In Bohemia Interactive regarding Arma 3, are hotfixes or completely new game content through DLC used for example. Similar is also done in Jagex in the form of hotpatches. Overall, the further development process is similar between the companies, through the different steps identified in this report. These can be described as an iterative process in which companies identify problems or proposals for further development, collect data or investigate existing data, implement the solution or proposal, collect feedback and act on the feedback.

During the 21st century, the use of digital services has exploded. Companies are getting better at collecting and using data for their own gain. The increased collection of data has contributed to increased privacy concerns among many. This paper examines how a person’s attitude and knowledge about data collection can affect their online behavior. To examine this, a questionnaire survey was conducted. The study's results indicate that there is a paradoxical behavior among the respondents, since most people have a negative view of data collection, but do not take measures to reflect this attitude. Furthermore, the result suggests that knowledge about data collection acts as the primary motivator for taking measures to protect their data.   Keywords: Data collection, online behaviour, privacy paradox, GDPR, attitude, knowledge, privacy concerns
Under 2000-talet har användningen av digitala tjänster exploderat. Företag blir bättre på att samla in och använda data för deras egen vinning. Den ökade datainsamlingen har bidragit till en ökad oro kring personlig data hos många. Denna uppsats undersöker hur internetanvändares attityd och kunskap kring datainsamling kan påverka deras online-beteende. För att undersöka detta utfördes en enkätundersökning. Studiens resultat indikerar att det finns ett paradoxalt beteende hos respondenterna då de flesta har en negativ syn till datainsamling men vidtar inte åtgärder för att spegla denna attityd. Vidare tyder resultatet på att kunskap kring datainsamling agerar som den primära motivatorn för att vidta åtgärder för att skydda deras data.   Nyckelord: Datainsamling, online-beteende, Privacy Paradox, GDPR, attityd, kunskap. integritets-oro

There is a fast increase of information and data generation in virtual environments due to microblogging sites such as Twitter, a social network that produces an average of 8, 000 tweets per second, and up to 550 million tweets per day. That's why this and many other social networks are overloaded with content, making it difficult for users to identify information topics because of the large number of tweets related to different issues. Due to the uncertainty that harms users who created the content, this study proposes a method for inferring the most representative topics that occurred in a time period of 1 day through the selection of user profiles who are experts in sports and politics. It is calculated considering the number of times this topic was mentioned by experts in their timelines. This experiment included a dataset extracted from Twitter, which contains 10, 750 tweets related to sports and 8, 758 tweets related to politics. All tweets were obtained from user timelines selected by the researchers, who were considered experts in their respective subjects due to the content of their tweets. The results show that the effective selection of users, together with the index of relevance implemented for the topics, can help to more easily find important topics in both sport and politics.

Authors augment their texts using devices such as bold and italic typeface to signal important information to the reader. These typographical text signals are an example of a signal designed to have some affect on others. However, some signals emerge through the unplanned, indirect, and collective efforts of a group of individuals. Paths emerge in parks without having been designed by anyone. Objects accumulate wear patterns that signal how others have interacted with the object. Books open to important, well studied pages because the spine has worn, for example (Hill, Hollan, Wroblewski, & McCandless, 1992). Digital text and the large-scale collaboration made possible through the internet provide an opportunity to examine how unplanned, collaborative text signals could emerge. A software application was designed, called CoREAD, that enables readers to highlight sections of the text they deem important. In addition, CoREAD adds text signals to the text using font colour, based on the group's collective history and an aggregation function based on self-organising systems. The readers are potentially influenced by the text signals presented by CoREAD but also help to modify these same signals. Importantly, readers only interact with each other indirectly through the text. The design of CoREAD was greatly inspired by the previous work on history-enriched digital objects (Hill & Hollan, 1993) and at a more general level it can be viewed as an example of distributed cognition (Hollan, Hutchins, & Kirsh, 2000).
Forty undergraduate students read two texts on topics from psychology using CoREAD. Students were asked to read each text in order to write a summary of it. After each new student read the text, the text signals were changed to reflect the current group of students. As such, each student read the text with different text signals presented.
The data were analysed for each text to determine if the text signals that emerged were stable and valid representations of the semantic content of the text. As well, the students' summaries were analysed to determine if students who read the text after the text signals had stabilised produced better summaries. Three methods demonstrated that CoREAD was capable of generating stable typographical text signals. The high importance text signals also appeared to capture the semantic content of the texts. For both texts, a summary made of the high signals performed as well as a benchmark summary. The results did not suggest that the stable text signals assisted readers to produce better summaries, however. Readers may not respond to these collaborative text signals as they would to authorial text signals, which previous research has shown to be beneficial (Lorch, 1989). The CoREAD project has demonstrated that readers can produce stable and valid text signals through an unplanned, self-organising process.

碩士
國立成功大學
電腦與通信工程研究所
105
In today's era of the Internet environment, there are many jobs we want to use an online platform to complete the jobs. However, in reality there are lots of data collection which are still using paper collection today. Therefore, we want to develop an online data-collecting system which is able to help data collection and meet any situation of data requirements. Therefore, we have designed an online interactive data collection system in an attempt to provide flexible data collection function. The design of the system can be divided into three parts. In the first part, to promote the usage of the system, we designed the system to adopt open authorization. Users can directly use the community website account to enter our system for data collection. The second part, we designed some mechanisms to enable users to set up what kinds of data that are needed to collect. Finally, we designed the system to allow the users to submit the data and to follow the data collection settings.

Sharing sensor data between multiple devices and users can be^challenging for naive users, and requires knowledge of programming and use of different communication channels and/or development tools, leading to non uniform solutions. This thesis proposes a system that allows users to access sensors, share sensor data and manage sensors. With this system we intent to manage devices, share sensor data, compare sensor data, and set policies to act based on rules. This thesis presents the design and implementation of the system, as well as three case studies of its use.
Universidade da Madeira