Abstract
More and more people are involved in sustainability-related activities through social network to support/protect their idea or motivation for sustainable development. Understanding the variety of issues of social pulsation is crucial in development of social sustainability. However, issues in social media generally change overtime. Issues not identified in advance may soon become popular topics discussed in society, particularly controversial issues. Previous studies have focused on the detection of hot topics and discussion of controversial issues, rather than the identification of potential controversial issues, which truly require paying attention to social sustainability. Furthermore, previous studies have focused on issue detection and tracking based on historical data. However, not all controversial issues are related to historical data to foster the cases. To avoid the above-mentioned research gap, Artificial Intelligence (AI) plays an essential role in issue detection in the early stage. In this study, an AI-based solution approach is proposed to resolve two practical problems in social media: (1) the impact caused by the number of fan pages from Facebook and (2) awareness of the levels for an issue. The proposed solution approach to detect potential issues is based on the popularity of public opinion in social media using a Web crawler to collect daily posts related to issues in social media under a big data environment. Some analytical findings are carried out via the congregational rules proposed in this research, and the solution approach detects the attentive subjects in the early stages. A comparison of the proposed method to the traditional methods are illustrated in the domain of green energy. The computational results demonstrate that the proposed approach is accurate and effective and therefore it provides significant contribution to upsurge green energy deployment.
Highlights
Sustainability is defined as “a process for creating sustainable places and participations” from the perspectives of social community [1] and social sustainability combines design with infrastructure to support social and cultural life, social amenities, systems for citizen in communities to evolve [2].there is a strong effect on information exchange and contribution, as well as exit intentions among social network site users, highlighting the important role of sense of community in the sustainability of social network sites [3]
This research makes the following two assumptions: (1) the method of this research only applies to Facebook, focusing on fan pages related to the domain of green energy and low carbon, and not including posts that belong to individual users; (2) only fan page members are available to Sustainability 2020, 12, 8057 follow issue posts on the fan page; this makes it easier to calculate participation explicitly
An Intelligent Controversial Issue Detection System (ICIDS) is configured to resolve the detection potential issues based on the popularity of the public opinions in social media, where the interaction between the ICIDS and the Users is presented, and the axioms used to detect potential controversial issues and the detection process are proposed
Summary
Sustainability is defined as “a process for creating sustainable places and participations” from the perspectives of social community [1] and social sustainability combines design with infrastructure to support social and cultural life, social amenities, systems for citizen in communities to evolve [2]. This research makes the following two assumptions: (1) the method of this research only applies to Facebook, focusing on fan pages related to the domain of green energy and low carbon, and not including posts that belong to individual users; (2) only fan page members are available to Sustainability 2020, 12, 8057 follow issue posts on the fan page; this makes it easier to calculate participation explicitly Based on these assumptions, an AI solution approach is proposed to resolve two practical problems relevant to the aforementioned weaknesses: (1) appraising the impact caused by the amount of fan pages from Facebook and (2) promoting awareness of the stages for an issue. This study improves the detection accuracy and generates predictable results, and enhances decision-makers’ abilities to judge “issues’ influences” through the proposing stage produced the coping strategies to provide decision-makers with corresponding strategies at the particular stages It assists organizations or enterprises in effective strategic planning, management, influence or control of the possible developing impact.
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