The Fundamentals of Policy Crowdsourcing

Prpić, John; Taeihagh, Araz; Melton, James

doi:10.31235/osf.io/wdtvh

Cited by 36 publications

(66 citation statements)

References 76 publications

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“…Adoption of many technological innovations, such as big data, waste incineration power plants, crowdsourcing, autonomous vehicles (AVs), the internet of things, and block-chain technology can cause new problems, since they often have unintended consequences and create new, previously inconceivable risks [27,28]. As a result of this, social acceptance of such innovative projects may be low [1,29].…”

Section: Risk In the Adoption Of Innovative Technologiesmentioning

confidence: 99%

The Governance of Risks in Ridesharing: A Revelatory Case from Singapore

Taeihagh

Jong

2018

Energies

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Abstract:Recently we have witnessed the worldwide adoption of many different types of innovative technologies, such as crowdsourcing, ridesharing, open and big data, aiming at delivering public services more efficiently and effectively. Among them, ridesharing has received substantial attention from decision-makers around the world. Because of the multitude of currently understood or potentially unknown risks associated with ridesharing (unemployment, insurance, information privacy, and environmental risk), governments in different countries apply different strategies to address such risks. Some governments prohibit the adoption of ridesharing altogether, while other governments promote it. In this article, we address the question of how risks involved in ridesharing are governed over time. We present an in-depth single case study on Singapore and examine how the Singaporean government has addressed risks in ridesharing over time. The Singaporean government has a strong ambition to become an innovation hub, and many innovative technologies have been adopted and promoted to that end. At the same time, decision-makers in Singapore are reputed for their proactive style of social governance. The example of Singapore can be regarded as a revelatory case study, helping us further to explore governance practices in other countries.

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Section: Risk In the Adoption Of Innovative Technologiesmentioning

confidence: 99%

The Governance of Risks in Ridesharing: A Revelatory Case from Singapore

Taeihagh

Jong

2018

Energies

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“…To date, user-generated Twitter data have been considered as real-time "social sensors" of public opinion (Crooks, Croitoru, Stefanidis, & Radzikowski, 2013;Preethi & Ajit kumar, 2015;Siqi, Lin, Jehan, & Venue, 2011;Weiler, Grossniklaus, & Scholl, 2015). Twitter data usually offer rich details on human behaviors and contextual factors in policy research, including textual information (e.g., the text message on a given policy), temporal information (e.g., the time at which the message is posted), and communication information (e.g., who talks with whom about the policy) (Chung & Zeng, 2015;Prpić, Taeihagh, & Melton, 2015). As such, social media data have already been used to gauge public opinion on an array of public policies, including, but not limited to, the U.S. immigration policy and border security (Chung & Zeng, 2015), space policy (Whitman, 2015), National Security Agency's surveillance programs (Reddicka, Chatfieldb, & Jaramilloa, 2015), climate change (Kirilenko & Stepchenkova, 2014), healthy food (Widener & Li, 2014), measles vaccination (Radzikowski, Stefanidis, Jacobsen, Croitoru, Crooks, & Delamater, 2016), to name a few.…”

Section: Social Media and Policy Researchmentioning

confidence: 99%

Common Core State Standards on Twitter: Public Sentiment and Opinion Leaders

Wang

Fikis

2017

Educational Policy

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The purpose of this study is to examine the public opinion on the Common Core State Standards (CCSS) on Twitter. Using Twitter API, we collected the tweets containing the hashtags #CommonCore and #CCSS for 12 months from 2014 to 2015. A Common Core corpus was created by compiling all the collected 660,051 tweets. The results of sentiment analysis suggest Twitter users expressed overwhelmingly negative sentiment towards the CCSS in all 50 states.Five topic clusters were detected by cluster analysis of the hashtag co-occurrence network. We also found that most of the opinion leaders were those who expressed negative sentiment towards the CCSS on Twitter. This study for the first time demonstrates how text mining techniques can be applied to education policy research, laying the foundation for real-time analytics of public opinion on education policies, thereby informing policymaking and implementation. , and #gagop) co-occurred in a tweet "Jeremy Spencer talking about the coming storm Nathan Deal will face with #CommonCore #gagov #StopCommonCore #gagop http://t.co/oyM0WIBBsw", then there were six co-occurrence ties connecting the four hashtags in the hashtag co-occurrence network: (1) CommonCore-gagov, (2) CommonCore-StopCommonCore, (3) CommonCore-gagop, (4) gagov-StopCommonCore; (5) gagovgagop; and (6) StopCommonCore-gagop. We wrote R code to repeat this procedure for all 660,051 tweets in the Common Core corpus to build the hashtag co-occurrence network. We then ran the faction algorithm-one of the network clustering algorithms-to partition the network (de Amorim, Barthélemy, & Ribeiro, 1992;Glover, 1989Glover, , 1990, thereby detecting the clusters of hashtags in the network. According to network science (Borgatti et al., 2013), the cooccurrence relationships between hashtags in the same cluster are closer than the ones in different clusters. Thus, the clusters of hashtags manifest the frequently co-occurred topics and their interconnections in the Common Core discourse on Twitter. Further, to ensure the robustness of network partitions, following the recommendations for cluster analysis, we ran the faction algorithm multiple times with different initial partitions by using different random number seeds (Borgatti et al., 2013). If the same subgroups always emerged, then the network partition is considered robust. Therefore, in this study we examined the subgroups that are consistently detected by using the faction algorithm. Communication Network AnalysisTo identify the opinion leaders in the Common Core discourse on Twitter, five centralities-Indegree, Outdegree, In-Bonacich Power, Out-Bonacich Power, and betweenness degree-were calculated as the indicators of each Twitter user's influence in the Twitter communication network. Opinion leaders, according to Rogers (2003), are those who occupy the PUBLIC SENTIMENT AND OPINION ON THE COMMON CORE 20 central structural locations in the communication network. In this study, the opinion leaders were those who have high centrality, calculated by performing social netwo...

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“…Also promoted by civil society organizations and academics are techniques such as deliberative democracy (Elster ; Dryzek ), deliberative polling (Fishkin and Luskin ), participatory budgeting (Miori and Russo ; Gilman ), consensus conferences (Andersen and Jæger ), citizen juries (Armour ), collaborative policymaking (Innes and Booher ), and crowdsourced policymaking (Dutil ; Prpić, Taeihagh and Melton ). Innovations such as these, in which real decision making authority is shared with those outside of government, are examples of new governance models that centre on the emergence of horizontal networks of public, private, and non‐profit organizations, superseding traditional hierarchical control by governments (Rhodes ).…”

Section: Evolving Engagement and Developing Technologymentioning

confidence: 99%

The evolution of citizen and stakeholder engagement in Canada, from Spicer to #Hashtags

Longo¹

2017

Can Public Adm

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Government‐led citizen and stakeholder engagement is undertaken with the broad aims of improving government effectiveness and strengthening perceived legitimacy for government action. However, some aspects of the digital era that are challenging and stretching these traditions include changing economics of attention, heightened expectations of citizens and stakeholders, and a reconfiguration of the nature of policymaking discourse. Seven Government of Canada citizen and stakeholder engagement cases, spread over the past 27 years, are reviewed against the emergence of digital technologies within the context of traditional engagement exercises to understand how governments are experimenting with new approaches, and how new models may still be needed to respond to this shifting technology landscape. A future research agenda is sketched that anticipates how expanding technological capabilities, changing expectations on the part of citizens and stakeholders, and new approaches to policy discourse might require a reappraisal of our concepts of citizen and stakeholder engagement.

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The Fundamentals of Policy Crowdsourcing

Cited by 36 publications

References 76 publications

The Governance of Risks in Ridesharing: A Revelatory Case from Singapore

The Governance of Risks in Ridesharing: A Revelatory Case from Singapore

Common Core State Standards on Twitter: Public Sentiment and Opinion Leaders

The evolution of citizen and stakeholder engagement in Canada, from Spicer to #Hashtags

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