Privacy Aware Monitoring of Mobile Users in Sensor Networks Environment

Jagdale, B. N.; Bakal, J. W.

doi:10.3991/ijim.v13i02.10023

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Everyone has an equal opportunity to express their mind regardless of their race, gender, or status in the real world [22]. Privacy and secrecy issues also have been highlighted in mobile apps/systems in education and business domains [23], [24]. In 2017 a survey on awareness of privacy has been conducted among Android users, which revealed that the level of understanding is still low [25] even though there is a raising need for privacy.…”

Section: Related Workmentioning

confidence: 99%

Anonymity Feature in Android Mobile Apps for Interest Groups

Yi¹,

Emran²,

Harum³

2021

IJACSA

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Mobile apps that provide platforms for interestoriented communities (or interest groups) allow people with common interests to gather virtually in sharing their shared passion and ideas. While the participation of such apps is voluntary, some people feel uncomfortable revealing their real identities due to privacy and safety concerns. Thus, some mobile apps provide an anonymity feature that allows people to join the group anonymously. Nevertheless, little is known on how the anonymity feature relates to the people who prefer to join interest groups. Thus in this paper, we hypothesize that mobile apps users that highly value interest groups will also highly appreciate the anonymity feature provided in the interest groups. In particular, we explored the market segment of mobile Android apps with anonymity features within selected interest groups. A pilot study was conducted where 34 Android apps users, primarily Malaysian, filled up the questionnaires designed to investigate the anonymity feature in the apps. The results of the pilot study show that most Android apps nowadays offer their users to remain anonymous. The findings show that most users who give a high score on the importance of interest-based groups also provide a high score on the importance of the anonymity feature offered by the mobile apps providers.

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Section: Related Workmentioning

confidence: 99%

Anonymity Feature in Android Mobile Apps for Interest Groups

Yi¹,

Emran²,

Harum³

2021

IJACSA

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“…The SCT mobile application allows user (entrepreneur and tourist/travelers) to assess their own private destination [24], then destination manager and government agencies able to access to view assessment result in each component via mobile application and also able to compare with others creative tourism destination (see Figure 3).…”

Section: Fig 3 Sct Assessment Mobile Application User Interfacementioning

confidence: 99%

Development of Mobile Application for Sustainable Creative Tourism Assessment using Confirmatory Factor Analysis Approach

Suphachaimongkol

Ratanatamskul

Silapacharanan

et al. 2019

Int. J. Interact. Mob. Technol.

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<span>Creative tourism has received increasing attention. At present, the concept of creative tourism is still in development stage since there are few or no indicators for assessing the potential of creative tourism to area-based sustainable goals. This document aims to introduce the process of mobile application for sustainable creative tourism (SCT) model development using confirmatory factor analysis (CFA) approach. The study was divided into 4 phases. The first phase involved establishing elements, indicators and criteria drawn from some previous studies and the opinions of experts’ judgement in this study. Secondly, indicators and criteria were selected by using Delphi technique. Thirdly, the indicators and criterias were confirmed by utilizing CFA, Finally, the prototype of SCT mobile application assessment tool is proposed for SCT in this study, based on CFA. Tools for the study included: 1) structured questionnaire from reviews of literature for interviewing the expert, 2) questionnaire for Delphi techniques among the experts for collecting an opinion about the selection of the indicators, and 3) a questionnaire to assess the possibility of data collection concerning the components and indicators of SCT. 300 samples from creative tourism enterprises from all around Thailand were collected and 253 were responded. Data analysis was conducted by using descriptive statistics and CFA. The study found that SCT model consists of 8 components and 36 indicators. The finding from our research shows that it is eligible to establish the novel SCT assessment indicators. The result of SCT application model is appropriate to develop mobile application for SCT assessment tool. </span>

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Study and analysis of various sentiment classification strategies: A challenging overview

Keakde

Muddana

2021

Int. J. Model. Simul. Sci. Comput.

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In large-scale social media, sentiment classification is a significant one for connecting gaps among social media contents as well as real-world actions, including public emotional status monitoring, political election prediction, and so on. On the other hand, textual sentiment classification is well studied by various platforms, like Instagram, Twitter, etc. Sentiment classification has many advantages in various fields, like opinion polls, education, and e-commerce. Sentiment classification is an interesting and progressing research area due to its applications in several areas. The information is collected from various people about social, products, and social events by web in sentiment analysis. This review provides a detailed survey of 50 research papers presenting sentiment classification schemes such as active learning-based approach, aspect learning-based method, and machine learning-based approach. The analysis is presented based on the categorization of sentiment classification schemes, the dataset used, software tools utilized, published year, and the performance metrics. Finally, the issues of existing methods considering conventional sentiment classification strategies are elaborated to obtain improved contribution in devising significant sentiment classification strategies. Moreover, the probable future research directions in attaining efficient sentiment classification are provided.

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Privacy Aware Monitoring of Mobile Users in Sensor Networks Environment

Cited by 3 publications

References 16 publications

Anonymity Feature in Android Mobile Apps for Interest Groups

Anonymity Feature in Android Mobile Apps for Interest Groups

Development of Mobile Application for Sustainable Creative Tourism Assessment using Confirmatory Factor Analysis Approach

Study and analysis of various sentiment classification strategies: A challenging overview

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