Determination of the satisfaction attribute in usability tests using sentiment analysis and fuzzy logic

被引:1
作者
Chanchi-Golondrino, Gabriel Elias [1 ]
Ospina-Alarcon, Manuel Alejandro [1 ]
Sierra-Martinez, Luz Marina [2 ]
机构
[1] Univ Cartagena, Fac Engn, Av Consulado,Cll 30 39B-192, Cartagena, Colombia
[2] Univ Cauca, Fac Elect Engn & Telecommun, Cll 5 4-70, Popayan, Colombia
关键词
fuzzy logic; satisfaction level; sentiment analysis; usability;
D O I
10.15837/ijccc.2023.3.4901
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the growth in the number of applications deployed in cloud app stores, usability has become a fundamental attribute to ensure end-user productivity and enterprise competitiveness. According to ISO 9241-11, the three attributes that determine the usability of a product are effectiveness, efficiency and satisfaction, the latter being the subjective attribute of usability. In conventional user tests, the satisfaction attribute is determined using perception questionnaires, being a challenge to determine this attribute more objectively, given the limitations of surveys in terms of veracity and subjectivity. Based on the above, in this article we propose as a contribution, the construction of a system based on fuzzy logic for the estimation of the usability satisfaction attribute in user tests, which has as inputs both the level of satisfaction obtained from the answers to the post-test questionnaire, and the level of satisfaction obtained from the polarities of the opinions of the test users, determined by means of sentiment analysis techniques. The proposed fuzzy system is intended to serve as a reference to be replicated at the academic and enterprise level in the conduct of usability tests and specifically in the more objective determination of the satisfaction attribute based on the advantages of fuzzy logic and sentiment analysis techniques.
引用
收藏
页数:14
相关论文
共 50 条
  • [31] Intelligent systems using fuzzy logic for the determination of breast tumors
    Cheng, XY
    Itoh, K
    Ohya, A
    Omoto, K
    Wang, Y
    Taniguchi, N
    Ogawa, S
    Akiyama, I
    PROCEEDINGS OF THE 20TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 20, PTS 1-6: BIOMEDICAL ENGINEERING TOWARDS THE YEAR 2000 AND BEYOND, 1998, 20 : 1356 - 1359
  • [32] Assessing the Job Satisfaction of Registered Nurses Using Sentiment Analysis and Clustering Analysis
    Jura, Matthew
    Spetz, Joanne
    Liou, Der-Ming
    MEDICAL CARE RESEARCH AND REVIEW, 2022, 79 (04) : 585 - 593
  • [33] Students' Satisfaction in Online Distance Learning using Fuzzy Logic and Inference System
    Najib, Liana
    Ahmad, Afida
    6TH IEEE INTERNATIONAL CONFERENCE ON RECENT ADVANCES AND INNOVATIONS IN ENGINEERING (ICRAIE), 2021,
  • [34] A Hybrid Multilingual Fuzzy-Based Approach to the Sentiment Analysis Problem Using SentiWordNet
    Madani, Youness
    Erritali, Mohammed
    Jamaa, Bengourram
    Sailhan, Francoise
    INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2020, 28 (03) : 361 - 390
  • [35] Sentiment Analysis of Students' Feedback on E-Learning Using a Hybrid Fuzzy Model
    Alzaid, Maryam
    Fkih, Fethi
    APPLIED SCIENCES-BASEL, 2023, 13 (23):
  • [36] Twitter sentiment analysis using fuzzy integral classifier fusion
    Emadi, Mehdi
    Rahgozar, Maseud
    JOURNAL OF INFORMATION SCIENCE, 2020, 46 (02) : 226 - 242
  • [37] Improving Usability in Mobile Apps for Residential Energy Management: A Hybrid Approach Using Fuzzy Logic
    Nunez, Ivonne
    Cano, Elia Esther
    Cruz, Edmanuel
    Concepcion, Dimas
    Navarro, Nila
    Rovetto, Carlos
    APPLIED SCIENCES-BASEL, 2024, 14 (05):
  • [38] Using sentiment analysis to review patient satisfaction data located on the internet
    Hopper, Anthony M.
    Uriyo, Maria
    JOURNAL OF HEALTH ORGANIZATION AND MANAGEMENT, 2015, 29 (02) : 221 - 233
  • [39] Low Frequency Keyword Extraction with Sentiment Classification and Cyberbully Detection Using Fuzzy Logic Technique
    Sheeba, J. I.
    Vivekanandan, K.
    2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2013, : 33 - 37
  • [40] Analysis of Computer Security Incidents Using Fuzzy Logic
    Vorobiev, E. G.
    Petrenko, S. A.
    Kovaleva, I. V.
    Abrosimov, I. K.
    PROCEEDINGS OF 2017 XX IEEE INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND MEASUREMENTS (SCM), 2017, : 369 - 371