Personalized recommendations in e-participation

Cantador, Iván; Bellogín, Alejandro; Cortés-Cediel, María E.; Gil, Olga

doi:10.1145/3127325.3127330

Cited by 24 publications

(12 citation statements)

References 16 publications

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“…Despite the arguments in favor and against (electronic) participative budgeting, and its benefits and limitations, there is a general agreement that nowadays the levels of citizen involvement in ePB processes are still low (Zheng and Schachter, 2017). Among the variety of elements that may influence this limited participation, several authors have highlighted issues related to the technical designs of the used e-platforms (Aragón et al, 2017;, and have proposed novel solutions in terms of content visualization and search and recommendation mechanisms (Cantador et al, 2017, to increase the citizens' engagement.…”

Section: Levels Of Discussion and Controversymentioning

confidence: 99%

“…Demographic and log data to address these questions are not publicly accessible for privacy regulations, but could be taken into account by the teams behind ePB platforms to enhance their reach and the overtime engagement of citizens. Among the variety of elements that may influence the levels of participation, several authors have discussed issues related to technical aspects of the used e-platforms (Aragón et al, 2017;, proposing novel solutions for content visualization, search and recommendation (Cantador et al, 2017, to increase the citizens' engagement.…”

Section: Discussionmentioning

confidence: 99%

“…In our study, even if two proposals addressed the same issue, they were treated in isolation. Providing mechanisms to automatically identify similar proposals is part of future work, and content-based similarities we already used in (Cantador et al, 2017) may be very valuable.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Exploiting Open Data to analyze discussion and controversy in online citizen participation

Cantador

Cortés-Cediel

Fernández

2020

Information Processing & Management

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In this paper we propose a computational approach that applies data mining techniques to analyze the citizen participation recorded in an online digital platform. Differently to previous work, the approach exploits external knowledge extracted from Open Government Data for processing the citizens' proposals and debates of the platform, enabling to characterize targeted issues and problems, and analyze the levels of discussion, support and controversy raised by the proposals. As a result of our analysis, we derive a number of insights and conclusions of interest and value for both citizens and government stakeholders in decision and policy making tasks. Among others, we show that proposals targeting issues that affect large majorities tend to be supported by citizens and ultimately implemented by the city council, but leave aside other very important issues affecting minority groups. Our study reveals that most controversial, likely relevant, problems do not always receive sufficient attention in e-participation. Moreover, it identifies several types of controversy, related to ideological and socioeconomic factors and political attitudes.

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Section: Levels Of Discussion and Controversymentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Exploiting Open Data to analyze discussion and controversy in online citizen participation

Cantador

Cortés-Cediel

Fernández

2020

Information Processing & Management

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“…In [79] author proposed user activity models for stackoverflow, Wenwo Forums & SinaWeibo to classify real experts. In [80] the model uses some basic features to compute the user weight. In this model the question-answer ratio is used to generate user weight, still, it ignores the consistency of the user.…”

Section: Literature Reviewmentioning

confidence: 99%

Web Page Ranking using Web Mining Techniques: A comprehensive survey

Sharma¹,

Yadav²

2021

Preprint

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<div>Purpose: Due to the exponential growth of internet users and internet traffic, information seekers are highly dependent upon search engines to extract relevant information. Due to the accessibility of a large amount of textual, audio, video etc. contents, the responsibility of search engines has increased.</div><div>Design/methodology/approach: The search engine provides relevant information to internet users concerning to their query; based on content, link structure etc. However, it does not provide the guarantee of the correctness of the information. The performance of a search engine is highly dependent upon the ranking module. The performance of the ranking module is dependent upon the link structure of web pages, which analyse through Web structure mining (WSM) and their content, which analyses through Web content mining (WCM). Web mining plays an important role in computing the rank of web pages.</div><div>Findings: In this article, web mining types, techniques, tools, algorithms and their challenges are presented. Further, it provides a critical comprehensive survey for the researchers by presenting different features of web pages, which are important to check the quality of web pages.</div><div>Originality: In this work, authors presented different approaches/techniques, algorithms and evaluation approaches in previous researches and identified some critical issues in page ranking & web mining, which provide future directions for the researchers, working in the area.</div>

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“…This scenario has many parallels with crowdsourcing platforms that are looking for a better matching between workers and tasks [5,7] and for a better quality of their service [2]. Examples of such tasks / contributions to recommend may consist of trusty hosts as in case of Couchsurfing 2 or companions in personal security solutions such as Companion 3 or social tasks like cleaning the garbage in the streets, helping elderly people doing grocery shopping, etc. Another example of services that can be viewed as collective good to recommend has been demonstrated in the work of Cantador et al [3] in which the authors present an study on recommending citizens' proposals on an e-participation platform that aim to address existing issues and problems in a city.…”

Section: What To Recommendmentioning

confidence: 99%

Recommender systems for citizens

Yang

Cantador

Nurbakova

et al. 2017

Proceedings of the International Workshop on Recommender Systems for Citizens

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This manifesto summarises the outcomes of the 1st Workshop on Recommender Systems for Citizens (CitRec'17), held at the 11th ACM Conference on Recommender Systems, in August 2017 in Como, Italy. We discuss challenges and opportunities for the development of recommender systems for citizens, including: the clarification of the role of recommender systems for cities and citizens; in this context, the identification of classes of items to be recommended; the need for targeting and engaging the right population, involving the right stakeholders; and the existence of underlying ethical issues such as fairness and consensus. We further provide an action plan to bring forward the research and application of recommender systems for citizens.

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Personalized recommendations in e-participation

Cited by 24 publications

References 16 publications

Exploiting Open Data to analyze discussion and controversy in online citizen participation

Exploiting Open Data to analyze discussion and controversy in online citizen participation

Web Page Ranking using Web Mining Techniques: A comprehensive survey

Recommender systems for citizens

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