Template-Type: ReDIF-Article 1.0
Author-Name: Abdul Orunsolu
Author-Name: Omorinola Afolabi
Author-Name: Simon Sodiya
Author-Name: Adio Akinwale
Title: A Users’ Awareness Study and Influence of Socio-Demography Perception of Anti-Phishing Security Tips
Abstract: Security tips are now used as a method of priming online users from falling prey for fraudulent scams. These security tips usually come as email, SMS or online posts where they can be easily accessed by the users. In this work, phishing attacks are simulated with varying cues that are available in such fraudulent email messages, SMS and web pages were used to investigate the effectiveness of the security tips used by Nigerian banks to prime their customers of online threats. A total of 427 respondents, purposively selected from three tertiary institutions in Ogun State, participated in the study. Each respondent was asked to identify five messages with varying phishing cues to evaluate their understanding of the security tips messages. The results which were computed at 95% Confidence Interval, indicated that 58.91% failed on the first attribute, 58.59% failed on the second attribute while 58.73% failed on the third attribute. 74.24% of the participant could not correctly identify a fake email message (fourth attribute) while 76.71% could not correctly identify a phished bank verification number update message (fifth attribute). Using the Mann Whitney Test, the result further showed that overall, those who failed the test are significantly more than those who passed. Moreover, a regression model is proposed to evaluate the influence of the socio demographic factors used in the study. This result indicated that gender, academic qualification and user's computer knowledge significantly influences their ability to recognize phished messages.
Keywords: Anti-phishing, User awareness, Security tips, Phishing cues, Electronic commerce
Pages: 138-151
Volume: 2018
Issue: 2
Year: 2018
File-URL: http://www.vse.cz/aip/download.php?jnl=aip&pdf=119.pdf
File-URL: https://aip.vse.cz/artkey/aip-201802-0001_a-users-8217-awareness-study-and-influence-of-socio-demography-perception-of-anti-phishing-security-tips.php
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Handle: RePEc:prg:jnlaip:v:2018:y:2018:i:2:id:119:p:138-151
X-File-Ref: http://www.vse.cz/RePEc/prg/jnlaip/references/119

Template-Type: ReDIF-Article 1.0
Author-Name: Lucie Šperková
Title: Review of Latent Dirichlet Allocation Methods Usable in Voice of Customer Analysis
Abstract: The aim of the article is to detect and review existing topic modelling methods of Latent Dirichlet Allocation and their modifications usable in Voice of Customer analysis. Voice of Customer is expressed mainly through textual comments which often focus on the evaluation of products or services the customer consumes. The most studied data source are customer reviews which contain next to the textual comments also ratings in form of scales. The aim of the topic models is to mine the topics and their aspects the customers are evaluating in their reviews and assign to them a particular sentiment or emotion. The author completed a systematic literature review of peer-reviewed published journal articles indexed in leading databases of Scopus and Web of Science and concerning the current use of Latent Dirichlet Allocation model variants in Voice of Customer textual analysis for performing the tasks of aspect detection, emotion detection, personality detection and sentiment assignation. In total, 38 modifications of the LDA model were identified with the reference to their first application in the research of text analytics. The review is intended for researchers in customer analytics the field of sentiment or emotion detection, and moreover as results from the review, for studies in personality recognition based on the textual data. The review offers a basic overview and comparison of LDA modifications which can be considered as a knowledge baseline for selection in a specific application. The scope of the literature examination is limited to the period of years 2003-2018 with the application relevant to the analysis of Voice of Customer subjective textual data only which is closely connected to the area of marketing or customer relationship management.
Keywords: Aspect detection, VoC, Topic models, Text analytics, Sentiment, LDA
Pages: 152-165
Volume: 2018
Issue: 2
Year: 2018
File-URL: http://www.vse.cz/aip/download.php?jnl=aip&pdf=120.pdf
File-URL: https://aip.vse.cz/artkey/aip-201802-0002_review-of-latent-dirichlet-allocation-methods-usable-in-voice-of-customer-analysis.php
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Handle: RePEc:prg:jnlaip:v:2018:y:2018:i:2:id:120:p:152-165
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Template-Type: ReDIF-Article 1.0
Author-Name: Petr Tesař
Title: Cryptocurrency
Abstract: This article is review of Jan Lansky's book "Cryptocurrency", which was published in the Czech language by C. H. Beck in 2018.
Keywords: review, recenze, Cryptocurrency, Book, Jan Lansky, Kryptoměny, kniha, Jan Lánský
Pages: 166-167
Volume: 2018
Issue: 2
Year: 2018
File-URL: http://www.vse.cz/aip/download.php?jnl=aip&pdf=121.pdf
File-URL: https://aip.vse.cz/artkey/aip-201802-0003_kryptomeny.php
File-Format: text/html
Handle: RePEc:prg:jnlaip:v:2018:y:2018:i:2:id:121:p:166-167
X-File-Ref: http://www.vse.cz/RePEc/prg/jnlaip/references/121