Modeling Crowd Feedback in the Mobile App Market

Mobile application (app) stores, such as Google Play and the Apple App Store, have recently emerged as a new model of online distribution platform. These stores have expanded in size in the past five years to host millions of apps, offering end-users of mobile software virtually unlimited options to choose from. In such a competitive market, no app is too big to fail. In fact, recent evidence has shown that most apps lose their users within the first 90 days after initial release. Therefore, app developers have to remain up-to-date with their end-users’ needs in order to survive. Staying close to the user not only minimizes the risk of failure, but also serves as a key factor in achieving market competitiveness as well as managing and sustaining innovation. However, establishing effective communication channels with app users can be a very challenging and demanding process. Specifically, users\u27 needs are often tacit, embedded in the complex interplay between the user, system, and market components of the mobile app ecosystem. Furthermore, such needs are scattered over multiple channels of feedback, such as app store reviews and social media platforms. To address these challenges, in this dissertation, we incorporate methods of requirements modeling, data mining, domain engineering, and market analysis to develop a novel set of algorithms and tools for automatically classifying, synthesizing, and modeling the crowd\u27s feedback in the mobile app market. Our analysis includes a set of empirical investigations and case studies, utilizing multiple large-scale datasets of mobile user data, in order to devise, calibrate, and validate our algorithms and tools. The main objective is to introduce a new form of crowd-driven software models that can be used by app developers to effectively identify and prioritize their end-users\u27 concerns, develop apps to meet these concerns, and uncover optimized pathways of survival in the mobile app ecosystem

Computational Abstraction of Films for Quantitave Analysis of Cinematography

Currently, film viewers’ options for getting objective information about films before watching them, are limited. Comparisons are even harder to find and often require extensive film knowledge both by the author and the reader. Such comparisons are inherently subjective, therefore they limit the possibilities for scalable and effective statistical analyses. Apart from trailers, information about films cannot reach viewers audibly or visibly, which seems absurd considering the very nature of film. The thesis examines repeatable quantification methods for computationally abstracting films in order to extract informative data for visualizations and further statistical analy- ses. Theoretical background empowered by multidisciplinary approach and design processes are described. Visualizations of analyses are provided and evaluated for their accuracy and efficiency. Throughout the thesis foundations for the future automated quantification player/plugin, are described aiming to facilitate further developments. Theoretical structures of the website which may act as a gateway that collects and provides data for statistical cinematic research are also discussed

Easy on that trigger dad: a study of long term family photo retrieval

We examine the effects of new technologies for digital photography on people's longer term storage and access to collections of personal photos. We report an empirical study of parents' ability to retrieve photos related to salient family events from more than a year ago. Performance was relatively poor with people failing to find almost 40% of pictures. We analyze participants' organizational and access strategies to identify reasons for this poor performance. Possible reasons for retrieval failure include: storing too many pictures, rudimentary organization, use of multiple storage systems, failure to maintain collections and participants' false beliefs about their ability to access photos. We conclude by exploring the technical and theoretical implications of these findings

Easy on that trigger dad: a study of long term family photo retrieval

We examine the effects of new technologies for digital photography on people's longer term storage and access to collections of personal photos. We report an empirical study of parents' ability to retrieve photos related to salient family events from more than a year ago. Performance was relatively poor with people failing to find almost 40% of pictures. We analyze participants' organizational and access strategies to identify reasons for this poor performance. Possible reasons for retrieval failure include: storing too many pictures, rudimentary organization, use of multiple storage systems, failure to maintain collections and participants' false beliefs about their ability to access photos. We conclude by exploring the technical and theoretical implications of these findings

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

Phoneme-based Video Indexing Using Phonetic Disparity Search

This dissertation presents and evaluates a method to the video indexing problem by investigating a categorization method that transcribes audio content through Automatic Speech Recognition (ASR) combined with Dynamic Contextualization (DC), Phonetic Disparity Search (PDS) and Metaphone indexation. The suggested approach applies genome pattern matching algorithms with computational summarization to build a database infrastructure that provides an indexed summary of the original audio content. PDS complements the contextual phoneme indexing approach by optimizing topic seek performance and accuracy in large video content structures. A prototype was established to translate news broadcast video into text and phonemes automatically by using ASR utterance conversions. Each phonetic utterance extraction was then categorized, converted to Metaphones, and stored in a repository with contextual topical information attached and indexed for posterior search analysis. Following the original design strategy, a custom parallel interface was built to measure the capabilities of dissimilar phonetic queries and provide an interface for result analysis. The postulated solution provides evidence of a superior topic matching when compared to traditional word and phoneme search methods. Experimental results demonstrate that PDS can be 3.7% better than the same phoneme query, Metaphone search proved to be 154.6% better than the same phoneme seek and 68.1 % better than the equivalent word search

An Exploration into Two Solutions to Propagating Web Accessibility for Blind Computer Users

A model is presented depicting the driving forces (Web industry, consumers, U.S. federal government, and technology) promoting an accessible Web and potential solutions within those forces. This project examines two distinct solutions, lawsuits (a consumer-driven solution) and AcceSS 2.1 transcoder (a technology-driven solution) to provide more information on two under-researched methods that could have far-reaching impacts on Web accessibility for the blind. First, an evaluation of the intraclass correlation (ICC) between homepage Web Accessibility Barrier (WAB) scores and WAB scores of levels 1-3 found that the homepage is not sufficient to detect the accessibility of the website. ICC of the homepage and average of levels 1-3 is 0.250 (p=0.062) and ICC of levels 1, 2, & 3 is 0.784 (p < 0.0001). Evaluating the homepage and first-level pages gives more accurate results of entire site accessibility. Second, an evaluation of the WAB scores of the homepage and first-level pages of websites of five companies sued for alleged inaccessible websites found mixed results: lawsuits worked in two cases, but didn't in three. This is seen through an examination of accessibility and complexity of the websites for years surrounding the lawsuits. Each sued website is compared to a control website within the same industry and to a random group of websites representing the general Web. Third, a usability study of the AcceSS 2.1 transcoding intermediary found that technology can increase users' efficiency, effectiveness, and satisfaction in Web interaction, regardless of universal design. The study entails a within-subject cross-over design wherein 15 users performed tasks on three websites: one universally designed, one non-universally designed, and one reference site. Paired t-tests examine the effect of AcceSS 2.1 on time, errors, and subjective satisfaction and mixed-model analysis examines the effect of study design on outcomes. Results show that users perform tasks faster, with fewer errors, and with greater satisfaction when accessing pages via AcceSS 2.1, but users where less satisfied with the universally designed website and significant differences were found in the universally designed website and not the non-universally designed website. Website usability and ease of navigation are more important to users than simple accessibility