Software Usability Evaluation Using Opinion Mining

El-Halees, Alaa M.

doi:10.4304/jsw.9.2.343-349

Cited by 24 publications

(12 citation statements)

References 7 publications

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“…For this purpose, a representative group of user have to write their opinion for certain software in three usability factors: effectiveness, efficiency and satisfaction. Then, these comments are analyzed using specialized techniques of Computer Science to determine how positive or negative are in each category [1].…”

Section: Opinion Miningmentioning

confidence: 99%

A Systematic Mapping Review of Usability Evaluation Methods for Software Development Process

Paz¹,

Pow-Sang

2016

IJSEIA

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Given that usability is one of the most important aspects of software quality, several methods have been developed in order to establish techniques capable of evaluating this attribute from early phases of the software development process. However, the choice of the most appropriate method for a particular scenario is still a difficult decision, due to the existence of a vast number of approaches that are described in the literature for this purpose. Therefore, a systematic mapping review was conducted in order to identify the most commonly used usability evaluation techniques in software developments. A total of 1169 studies were identified, of which only 215 studies were selected for this review. According to the analysis, most cases studies establish the use of usability questionnaires as assessment tool. In addition, health informatics and Web applications are the software domain and type of application that are frequently reported in these evaluations. This work has allowed to reach promising results in this area. It is intended to be a guide for specialists to support the choice of the most suitable method for a particular scenario.

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Section: Opinion Miningmentioning

confidence: 99%

A Systematic Mapping Review of Usability Evaluation Methods for Software Development Process

Paz¹,

Pow-Sang

2016

IJSEIA

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“…Berkaitan dengan evaluasi faktor usability, El Hales dalam penelitiannya pernah menggunakan model usability pada ISO 9241-1 yang meliputi effectiveness, efficiency dan satisfaction sebagai faktor untuk mengevaluasi usability perangkat lunak. Metode yang digunakan dalam penelitian tersebut adalah opinion mining atau penambangan opini (El-Halees, 2014). Kemudian dengan menentukan orientasi sentimen berdasarkan metode opinion mining, opini pengguna akan diklasifikasikan ke dalam orientasi positif, negatif atau netral (Sharma & Chitre, 2014).…”

Section: Pendahuluanunclassified

Klasifikasi Multi Class Pada Analisis Sentimen Opini Pengguna Aplikasi Mobile Untuk Evaluasi Faktor Usability

Wardhana

Purwitasari

2019

Journal Of Information Technology

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Dalam proses pengembangan maupun pengujian perangkat lunak, faktor usability merupakan aspek yang paling penting. Evaluasi faktor usability tersebut dapat dilakukan dengan menganalisa orientasi sentimen pada opini pengguna berdasarkan faktor usability. Namun, setiap opini juga memiliki tingkat sentimen yang mencerminkan tinggi rendahnya orientasi sentimen, sehingga akan lebih efektif apabila tingkat sentimen juga dipertimbangkan dalam proses evaluasi. Selain itu, opini pengguna juga dapat memiliki lebih dari 1 faktor usability. Hal tersebut dikarenakan setiap dokumen opini dapat terdiri lebih dari 1 kalimat dimana setiap kalimat bisa memiliki faktor usability yang berbeda. Berbeda dengan perangkat lunak lainnya, aplikasi mobile memiliki batasan dan konteks tersendiri. Sehingga model usability yang digunakan juga berbeda dengan perangkat lunak lainnya. Model PACMAD merupakan model usability yang disesuaikan dengan batasan dan konteks dari aplikasi mobile. Oleh karena itu dalam penelitian ini diusulkan suatu metode evaluasi faktor usability dengan menggunakan klasifikasi multi class pada analisis sentimen dengan mempertimbangkan tingkat sentimen opini pengguna aplikasi mobile berdasarkan model usability PACMAD. Data opini pengguna dikaslifikasian dengan model klasifikasi multi class dengan metode naive bayes, kemudian dianalisis orientasi dan tingkat sentimennya dengan menggunakan metode SentiWordNet Interpretation. Berdasarkan hasil ujicoba diperoleh nilai akurasi sebesar 74,7%, precision 43,2%, recall 29,5% dan f-measure 34,5%.

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“…SentBuk, a Facebook application that retrieves messages written by users in Facebook and classifies them according to their polarity, showing the results to the users through an interactive interface . Finally, a research team used OM as an automatic technique to evaluate subjective usability .…”

Section: Related Workmentioning

confidence: 99%

Opinion mining and emotion recognition in an intelligent learning environment

Bustillos

Zataraín-Cabada

Barrón-Estrada

et al. 2018

Comp Applic In Engineering

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In this paper, we present the development of an opinion‐mining module. The development of the module consisted of creating an emotion tagged dataset of opinions; implementing an opinion mining module that processes sentences about computer programming, predicting or recognizing their polarity (positive/negative) and their type of emotion (frustrated, bored, excited, engagement, and neutral); and integrating the previous module in an intelligent learning environment. We evaluated the corpus, the accuracy of text polarity, and emotion recognition. The results with respect to polarity are promising (88.26%), however, the results in the detection of emotions are still low (60.0%). The reasons which likely explain these outcomes include a relatively small (7,777 records) and unbalanced corpus.

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Software Usability Evaluation Using Opinion Mining

Cited by 24 publications

References 7 publications

A Systematic Mapping Review of Usability Evaluation Methods for Software Development Process

A Systematic Mapping Review of Usability Evaluation Methods for Software Development Process

Klasifikasi Multi Class Pada Analisis Sentimen Opini Pengguna Aplikasi Mobile Untuk Evaluasi Faktor Usability

Opinion mining and emotion recognition in an intelligent learning environment

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