Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
102 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Appsent A Tool That Analyzes App Reviews (1907.10191v1)

Published 24 Jul 2019 in cs.SE

Abstract: Enterprises are always on the lookout for tools that analyze end-users perspectives on their products. In particular, app reviews have been assessed as useful for guiding improvement efforts and software evolution, however, developers find reading app reviews to be a labor intensive exercise. If such a barrier is eliminated, however, evidence shows that responding to reviews enhances end-users satisfaction and contributes towards the success of products. In this paper, we present Appsent, a mobile analytics tool as an app, to facilitate the analysis of app reviews. This development was led by a literature review on the problem and subsequent evaluation of current available solutions to this challenge. Our investigation found that there was scope to extend currently available tools that analyze app reviews. These gaps thus informed the design and development of Appsent. We subsequently performed an empirical evaluation to validate Appsent usability and the helpfulness of analytics features from users perspective. Outcomes of this evaluation reveal that Appsent provides user-friendly interfaces, helpful functionalities and meaningful analytics. Appsent extracts and visualizes important perceptions from end-users feedback, identifying insights into end-users opinions about various aspects of software features. Although Appsent was developed as a prototype for analyzing app reviews, this tool may be of utility for analyzing product reviews more generally.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Saurabh Malgaonkar (2 papers)
  2. Chan Won Lee (3 papers)
  3. Sherlock A. Licorish (36 papers)
  4. Bastin Tony Roy Savarimuthu (16 papers)
  5. Amjed Tahir (34 papers)

Summary

We haven't generated a summary for this paper yet.