Enriching iTunes App Store Categories via Topic Modeling

Mobile application development is an emerging lucrative and fast growing market. With the steady growth of the number of apps in the repositories the providers will inevitably face the need to fine-grain the existing hierarchy of categories used to organize the apps. In this paper we present a method to bootstrap the categorization process via topic modeling. We apply Latent Dirichlet Allocation (LDA) to the textual descriptions of iTunes apps in order to identify recurrent topics in the collection. We evaluate and discuss the results obtained from training the model on a set of almost 600,000 English-language app descriptions. Our results demonstrate that automated categorization via LDA-based topic modeling is a promising approach, that can help to structure, analyze and manage the content of app repositories. The topics produced complement the original iTunes categories, concretize and extend them by providing insights into the underlying category content

Topic Embeddings – A New Approach to Classify Very Short Documents Based on Predefined Topics

Traditional unsupervised topic modeling approaches like Latent Dirichlet Allocation (LDA) lack the ability to classify documents into a predefined set of topics. On the other hand, supervised methods require significant amounts of labeled data to perform well on such tasks. We develop a new unsupervised method based on word embeddings to classify documents into predefined topics. We evaluate the predictive performance of this novel approach and compare it to seeded LDA. We use a real-world dataset from online advertising, which is comprised of markedly short documents. Our results indicate the two methods may complement one another well, leading to remarkable sensitivity and precision scores of ensemble learners trained thereupon

The Dimensions of Review Comprehensiveness and Its Effect on Review Usefulness: A Latent Dirichlet Allocation Approach

Online review sites like Yelp.com, TripAdvisor.com and AngiesList.com provide values to both business and consumers. A large body of literature investigates drivers of online review usefulness. Review comprehensiveness has been identified as one the most important dimension of review quality and an important predictor of review usefulness. This study contributes to the literature by crafting and operationalizing review comprehensiveness using a text mining approach. We also empirically test the effect of the operationalized review comprehensiveness construct on review usefulness. In practice, online review providers, especially Yelp.com, can benefit from this study by integrating review comprehensiveness in their sorting algorithms

Leveraging Mobile App Classification and User Context Information for Improving Recommendation Systems

Mobile apps play a significant role in current online environments where there is an overwhelming supply of information. Although mobile apps are part of our daily routine, searching and finding mobile apps is becoming a nontrivial task due to the current volume, velocity and variety of information. Therefore, app recommender systems provide users’ desired apps based on their preferences. However, current recommender systems and their underlying techniques are limited in effectively leveraging app classification schemes and context information. In this thesis, I attempt to address this gap by proposing a text analytics framework for mobile app recommendation by leveraging an app classification scheme that incorporates the needs of users as well as the complexity of the user-item-context information in mobile app usage pattern. In this recommendation framework, I adopt and empirically test an app classification scheme based on textual information about mobile apps using data from Google Play store. In addition, I demonstrate how context information such as user social media status can be matched with app classification categories using tree-based and rule-based prediction algorithms. Methodology wise, my research attempts to show the feasibility of textual data analysis in profiling apps based on app descriptions and other structured attributes, as well as explore mechanisms for matching user preferences and context information with app usage categories. Practically, the proposed text analytics framework can allow app developers reach a wider usage base through better understanding of user motivation and context information

A survey of app store analysis for software engineering

App Store Analysis studies information about applications obtained from app stores. App stores provide a wealth of information derived from users that would not exist had the applications been distributed via previous software deployment methods. App Store Analysis combines this non-technical information with technical information to learn trends and behaviours within these forms of software repositories. Findings from App Store Analysis have a direct and actionable impact on the software teams that develop software for app stores, and have led to techniques for requirements engineering, release planning, software design, security and testing. This survey describes and compares the areas of research that have been explored thus far, drawing out common aspects, trends and directions future research should take to address open problems and challenges

POPULARITY AND AUDIENCE MEASUREMENT OF MOBILE APPS: ENABLING EFFECTIVE MOBILE ADVERTISEMENT

Ph.DDOCTOR OF PHILOSOPH

Clustering and Topic Modelling: A New Approach for Analysis of National Cyber security Strategies

The consequences of cybersecurity attacks can be severe for nation states and their people. Recently many nations have revisited their national cybersecurity strategies (NCSs) to ensure that their cybersecurity capabilities is sufficient to protect their citizens and cyberspace. This study is an initial attempt to compare NCSs by using clustering and topic modelling methods to investigate the similarity and differences between them. We also aimed to identify underlying topics that are appeared in NCSs. We have collected and examined 60 NCSs that have been developed during 2003-2016. By relying on institutional theories, we found that memberships in the international intuitions could be a determinant factor for harmonization and integration between NCSs. By applying hierarchical clustering method, we noticed a stronger similarities between NCSs that are developed by the EU or NATO members. We also found that public-private partnerships, protection of critical infrastructure, and defending citizen and public IT systems are among those topics that have been received considerable attention in the majority of NCSs. We also argue that topic modeling method, LDA, can be used as an automated technique for analysis and understanding of textual documents by policy makers and governments during the development and reviewing of national strategies and policies

Definição de modelo de reconhecimento de entidade nomeada para detecção automática de tópicos de aplicativos em português

TCC (graduação) - Universidade Federal de Santa Catarina, Centro Tecnológico, Ciências da Computação.Com as mudanças sociais e tecnológicas presentes ao longo dos séculos, a criatividade passou a ser considerada essencial. Uma alternativa para o desenvolvimento da criatividade ainda na educação básica se dá por meio do estudo da área da computação com o desenvolvimento de artefatos computacionais, como por exemplo aplicativos móveis com App Inventor. Nesse contexto, é importante a avaliação da aprendizagem do aluno também em relação ao desenvolvimento da criatividade. Considerando a originalidade como uma das principais dimensões da criatividade, visa-se assim realizar a avaliação da originalidade dos aplicativos criados com App Inventor em relação aos tópicos que abordam. Usando como entrada para essa análise os elementos textuais extraídos dos apps, a classificação desses tópicos pode ser melhorada com o uso do Reconhecimento de Entidade Nomeada (NER - Named Entity Recognition). O NER é uma técnica de computação dentro da área de Processamento de Linguagem Natural (NLP - Natural Language Processing) 60 que permite que entidades sejam reconhecidas automaticamente a partir de palavras e frases. Dessa maneira, este trabalho tem como objetivo desenvolver um modelo de NER em português para identificação de entidades a fim de auxiliar na classificação automática de tópicos de aplicativos móveis criados com App Inventor. Com isso, espera-se contribuir para a avaliação da originalidade dos aplicativos criados pelos alunos, contribuindo assim também para o ensino da computação nas escolas do paísWith the social and technological changes, creativity has come to be considered essential. An alternative for the development of creativity even in K-12 is through the study of computing by developing computational artifacts, for example, mobile applications with App Inventor. In this context, it is important to evaluate the student's learning also in relation to the development of creativity. Considering originality one of the main dimensions of creativity, the aim is to evaluate the originality of applications created with App Inventor in relation to the topics they address. Using as input for this analysis the textual elements extracted from the apps, the classification of these topics can be improved with the use of Named Entity Recognition (NER). NER is a computing technique within the field of Natural Language Processing (NLP) that allows entities to be automatically recognized from words and phrases. Thus, this work aims to develop a NER model in Portuguese for entity identification in order to assist in the automatic classification of mobile application topics created with App Inventor. With this, it is expected to contribute to the evaluation of the originality of the applications created by the students, thus also contributing to the teaching of computing in schools in the country

Exploring Multi-Sensory Curriculum Development: Grades 3-5 Science In A Virtual Environment

The capstone thesis uses a qualitative research approach to explore the question: What are virtual tools and multi-sensory strategies that can be integrated into curriculum development to support the engagement of learners in science in grades 3-5 in virtual learning environments? The author chose this topic to find and to apply multi-sensory strategies, including technology-rich approaches, in virtual education, and developed a new curriculum unit using current sensory-rich technologies. The goal is to enhance and enrich curriculum, and thereby to increase student engagement in the sciences. Applying these tools in virtual education and using multi-sensory approaches can lead to new possibilities. The possibilities of using virtual and augmented reality tools is examined in relationship to the content area. Topics explored in the review of the literature include Gardner, Dewey, Montessori, Piaget, and virtual education using virtual reality, augmented reality, and programs and applications for virtual and face-to-face classrooms. The limitations and dangers of these tools, as well as their benefits, are discussed. Understanding by Design (UbD) and a constructivist teaching approach, and an integrated approach using these technologies, are used to develop a unit of science curriculum in Ocean Science, refreshed from a successful traditional unit. The author finds the multiple intelligences and the sensory approaches from Gardner and the multi-sensory, constructivist approaches most pivotal. Montessori seems to be the most knowledgeable about the importance of multi-sensory education itself. Integrating technological applications, including virtual reality (VR), augmented reality (AR) applications, and examining ongoing research, proves productive. The field of technology in education is an ever-changing and ever-expanding field. The author suggests it may be effective within a school system, district and classroom to develop a technology and curriculum review team to face the many decisions, challenges, and changes technology in the classroom brings. The author concludes that to broaden multi-sensory approaches, used in any form, in any educational environment, will benefit every student. For the developed curriculum, the limitations, implications, and recommendations for future research are discussed

The Tale of e-Government: A Review of the Stories that Have Been Told So Far and What is Yet to Come

Since its first appearance, the concept of e-Government has evolved into a recognized means that has helped the public sector to increase its efficiency and effectiveness. A lot of research has therefore been done in this area to elaborate on the different aspects encompassing this concept. However, when looking at the existing e-Government literature, research mostly focuses on one specific aspect of e-Government and there are few generic publications that provide an overview of the diversity of this interdisciplinary research field over a longer term period. This study analyzes the abstracts of eight e-Government journals from 2000 to 2016 by means of a quantitative text mining analysis, backed by a qualitative Delphi approach. The article concludes with a discussion on the findings and implications as well as directions for future research