Beyond the Stars: Towards a Novel Sentiment Rating to Evaluate Applications in Web Stores of Mobile Apps

@article{Rodrigues2017BeyondTS,
  title={Beyond the Stars: Towards a Novel Sentiment Rating to Evaluate Applications in Web Stores of Mobile Apps},
  author={Phillipe Rodrigues and Ismael Santana Silva and Gl{\'i}via Ang{\'e}lica Rodrigues Barbosa and Fl{\'a}vio R. S. Coutinho and Fernando Mour{\~a}o},
  journal={Proceedings of the 26th International Conference on World Wide Web Companion},
  year={2017}
}
This paper proposes an approach to evaluate mobile applications which complements the information provided by the number of stars and downloads in app stores. The goal is to provide novel information to assist users in the decision-making process regarding the choice of applications. In this sense, we conducted experiments to verify the relationship between the number of stars and the content of review comments. Results indicated that there is information in reviews not properly represented by… 

Figures and Tables from this paper

A Feature-Oriented Sentiment Rating for Mobile App Reviews

TLDR
A general framework that allows developers to filter, summarize and analyze user reviews written about applications on App Stores is proposed, which shows that the topic modeling block is able to organize information provided by users in subcategories that facilitate the understanding of which features more positively/negatively impact the overall evaluation of the application.

What People Like in Mobile Finance Apps: An Analysis of User Reviews

TLDR
How different aspects of mobiles apps affect their ratings is illustrated, how this varies across sub-categories, and the role of privacy, user interfaces, signup experiences, notifications, when the use of location services may be appropriate are discussed.

Please please me: does the presence of test cases influence mobile app users' satisfaction?

TLDR
This paper probed into whether there is a relation between having automated tests and overall user satisfaction, and looked into users ratings, which express their level of satisfaction with apps, and users reviews, which often include bug reports.

Quality Prediction of Wearable Apps in the Google Play Store

TLDR
A regression model is proposed that has a wide range of recommended features, including sentiment, content similarity, language and time features, to detect wearable applications in the Play Store and is most suitable for deep neural network (DNN) training.

Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification

TLDR
A novel representation learning method is proposed that uses emoji prediction as an instrument to learn respective sentiment-aware representations for each language that are integrated to facilitate cross-lingual sentiment classification.

Aplikasi Edutainment Pendukung Pembelajaran Jarak Jauh TK Merujuk Standar Nasional PAUD

Pandemi COVID-19 memicu perubahan pembelajaran Nasional, memunculkan “Belajar Dari Rumah”. Penyelenggaraan Pendidikan menjadi Pembelajaran Jarak Jauh (PJJ), tidak terkecuali untuk jenjang Taman

Mobile Media Usability

TLDR
The industry’s answer to this problem is this problem, which means the creation of a device-agnostic media-delivery techniques and increasedusability.

References

SHOWING 1-10 OF 31 REFERENCES

Awesome!: conveying satisfaction on the app store

TLDR
This work reports on an analysis of reviews to determine how closely aligned the numerical ratings are to the textual description, and observed that short user reviews mostly contain a small set of words, and the corresponding numerical rating matches the underlying sentiment.

Leveraging User Reviews to Improve Accuracy for Mobile App Retrieval

TLDR
This work jointly model app descriptions and user reviews using topic model in order to generate app representations while excluding noise in reviews and indicates that the proposed approach is effective and outperforms the state-of-the-art retrieval models for app retrieval.

A preliminary analysis of mobile app user reviews

TLDR
In this preliminary study, a analysis of 8.7 million reviews from 17,330 apps shows that users tend to leave short, yet informative reviews, and the rating as well as the category influences the length of a review.

Opinion-based entity ranking

TLDR
This paper proposes a different way of leveraging opinionated content, by directly ranking entities based on a user’s preferences, which is to represent each entity with the text of all the reviews of that entity.

Mining and summarizing customer reviews

TLDR
This research aims to mine and to summarize all the customer reviews of a product, and proposes several novel techniques to perform these tasks.

Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales

TLDR
A meta-algorithm is applied, based on a metric labeling formulation of the rating-inference problem, that alters a given n-ary classifier's output in an explicit attempt to ensure that similar items receive similar labels.

App recommendation: a contest between satisfaction and temptation

TLDR
This work proposes an Actual- Tempting model that captures factors that invoke a user to replace an old app with a new app and shows that the AT model performs significantly better than the conventional recommendation techniques such as collaborative filtering and content-based recommendation.

Effective sentiment stream analysis with self-augmenting training and demand-driven projection

TLDR
The heart of the approach is a training augmentation procedure which takes as input a small training seed, and then it automatically incorporates new relevant messages to the training data, so that at any given time the model properly reflects the sentiments in the event being analyzed.

Extracting usability and user experience information from online user reviews

TLDR
The results suggest that a greater understanding of users' preoccupation with different dimensions of usability and UX may be inferred from the large volume of self-reported experiences online, and that research focused on identifying pertinent dimensions of UX may benefit further from empirical studies of user-generated experience reports.

Accessibility in smartphone applications: what do we learn from reviews?

TLDR
The main goal was to analyze the contents of the reviews to infer the presence and polarity of accessibility information, which would be useful in application ranking based on accessibility features and improve the users' interaction experiences.