Active and Passive Crowdsourcing in Government

Loukis, Euripidis N.; Charalabidis, Yannis

doi:10.1007/978-3-319-12784-2_12

Cited by 29 publications

(19 citation statements)

References 26 publications

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“…The literature reports extensive studies that have been carried out to measure public opinion on different issues and policies through computational-based opinion mining methods. There is growing interest in opinion mining applications to analyze political issues due to the already vast and constantly increasing creation of political content on the Web and its exchange, particularly on social media networks and platforms [16][17][18]. The underlying principle in such studies is that the analysis of public opinions expressed on social media networks and platforms, if well done, "can be quite useful for government agencies, as it can significantly assist them to understand the needs and problems of society, and the perceptions and feelings of the citizens, and to formulate effective public policies" [16].…”

Section: Previous Workmentioning

confidence: 99%

Opinion Mining of Saudi Responses to COVID-19 Vaccines on Twitter

Alliheibi¹,

Omar²,

Al-Horais³

2021

IJACSA

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In recent months, many governments have announced COVID-19 vaccination programs and plans to help end the crises the world has been facing since the emergence of the coronavirus pandemic. In Saudi Arabia, the Ministry of Health called for citizens and residents to take up the vaccine as an essential step to return life to normal. However, the take-up calls were made in the face of profound disagreements on social media platforms and online networks about the value and efficacy of the vaccines. Thus, this study seeks to explore the responses of Saudi citizens to the COVID-19 vaccines and their sentiments about being vaccinated using opinion mining methods to analyze data extracted from Twitter, the most widely used social media network in Saudi Arabia. A corpus of 37,467 tweets was built. Vector space classification (VSC) methods were used to group and categorize the selected tweets based on their linguistic content, classifying the attitudes and responses of the users into three defined categories: positive, negative, and neutral. The lexical semantic properties of the posts show a prevalence of negative responses. This indicates that health departments need to ensure citizens are equipped with accurate, evidence-based information and key facts about the COVID-19 vaccines to help them make appropriate decisions when it comes to being vaccinated. Although the study is limited to the analysis of attitudes of people to the COVID-19 vaccines in Saudi Arabia, it has clear implications for the application of opinion mining using computational linguistic methods in Arabic.

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Section: Previous Workmentioning

confidence: 99%

Opinion Mining of Saudi Responses to COVID-19 Vaccines on Twitter

Alliheibi¹,

Omar²,

Al-Horais³

2021

IJACSA

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“…Active crowdsourcing platforms have been developed for users to enthusiastically contribute the required information [63][64][65]. These platforms are usually developed and implemented by members of the affected public, or by non-governmental organizations (NGO's) such as Ushahidi (https:// www.ushahidi.com/).…”

Section: Crowdsourcingmentioning

confidence: 99%

Big Data in Natural Disaster Management: A Review

2018

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Undoubtedly, the age of big data has opened new options for natural disaster management, primarily because of the varied possibilities it provides in visualizing, analyzing, and predicting natural disasters. From this perspective, big data has radically changed the ways through which human societies adopt natural disaster management strategies to reduce human suffering and economic losses. In a world that is now heavily dependent on information technology, the prime objective of computer experts and policy makers is to make the best of big data by sourcing information from varied formats and storing it in ways that it can be effectively used during different stages of natural disaster management. This paper aimed at making a systematic review of the literature in analyzing the role of big data in natural disaster management and highlighting the present status of the technology in providing meaningful and effective solutions in natural disaster management. The paper has presented the findings of several researchers on varied scientific and technological perspectives that have a bearing on the efficacy of big data in facilitating natural disaster management. In this context, this paper reviews the major big data sources, the associated achievements in different disaster management phases, and emerging technological topics associated with leveraging this new ecosystem of Big Data to monitor and detect natural hazards, mitigate their effects, assist in relief efforts, and contribute to the recovery and reconstruction processes.

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“…SMM has been defined as the continuous, systematic observation and analysis of SM networks and social communities (Fensel et al, 2012;Bekkers et al, 2013). Using SMM, the government can passively monitor SM communities related to a specific topic or policy (Loukis & Charalabidis, 2015;Loukis et al, 2017). However, to access knowledge from SM content, SMM is not enough.…”

Section: Citizens' Engagement Through Sm For Policy Co-designmentioning

confidence: 99%

Do policymakers use social media for policy design? A Twitter analytics approach

Rathore

Maurya

Srivastava

2021

AJIS

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Social media has been used widely for communicating information, awareness, and promote public policies by government agencies. However, limited attention has been paid to the use of social media in improving the design of public policies. This paper explores to what extent citizens' responses/opinions expressed on social media platforms contribute to policy design. The paper analyzes discussion about the 'Ayushman Bharat' scheme on Twitter through social media analytics techniques (e.g., content analytics) and then traces the change in policy design over two years. To validate findings from Twitter data, and assess the evolution in policy design, we conducted in-depth interviews with experts and extensive document analysis. The paper reveals that consistently similar issues were raised by the experts in the past as well as by the citizens in the current scheme. However, over the period, the policy design has not changed significantly. Therefore, despite a strong social media presence, its optimum use to improve policy effectiveness is yet to be achieved. The paper contributes by exploring the role social media can play in the public policy process and policy design in developing countries' contexts and identifies gaps in existing social media strategies of public agencies.

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Active and Passive Crowdsourcing in Government

Cited by 29 publications

References 26 publications

Opinion Mining of Saudi Responses to COVID-19 Vaccines on Twitter

Opinion Mining of Saudi Responses to COVID-19 Vaccines on Twitter

Big Data in Natural Disaster Management: A Review

Do policymakers use social media for policy design? A Twitter analytics approach

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