A Framework for App Store Optimization

05/28/2019
by   Artur Strzelecki, et al.
0

In this paper a framework for app store optimization is proposed. The framework is based on two main areas: developer dependent elements and user dependent elements. Developer dependent elements are similar factors in search engine optimization. User dependent elements are similar to activities in social media. The proposed framework is modelled after downloading sample data from two leading app stores: Google Play and Apple iTunes. Results show that developer dependent elements can be better optimized. Names and descriptions of mobile apps are not fully utilized.

READ FULL TEXT

Authors

page 6

10/04/2020

Understanding Incentivized Mobile App Installs on Google Play Store

"Incentivized" advertising platforms allow mobile app developers to acqu...
12/02/2019

Addict Free – A Smart and Connected Relapse Intervention Mobile App

It is widely acknowledged that addiction relapse is highly associated wi...
06/20/2022

The Cost of the GDPR for Apps? Nearly Impossible to Study without Platform Data

A recently published pre-print titled 'GDPR and the Lost Generation of I...
05/25/2019

An Exploratory Study on Machine Learning Model Stores

Recent advances in Artificial Intelligence, especially in Machine Learni...
02/22/2017

Social Learning and Diffusion of Pervasive Goods: An Empirical Study of an African App Store

In this study, the authors develop a structural model that combines a ma...
12/31/2017

Learning Continuous User Representations through Hybrid Filtering with doc2vec

Players in the online ad ecosystem are struggling to acquire the user da...
01/17/2018

The Socket Store: An App Model for the Application-Network Interaction

A developer of mobile or desktop applications is responsible for impleme...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.