2017 · 41 citations · 25 references
Crowd ComputingComputational Social ScienceSocial MediaEngineeringData ScienceSocial Medium MonitoringParticipatory SensingSocial ComputingEmergency Relief ScenarioHuman-computer InteractionMobile ComputingCommunicationCrowdsourcingLanguage StudiesContent AnalysisSocial Media-based ParadigmHybrid CrowdsensingSocial Medium Mining
Crowdsensing systems can be either participatory or opportunistic, depending on whether the user intentionally contributes data, or she simply acts as the bearer of a sensing device from which data is transparently collected. In this paper, we propose hybrid crowdsensing, a social media-based paradigm which aims at combining the strengths of both participatory and opportunistic crowdsensing. With hybrid crowdsensing, possibly relevant data is collected via an opportunistic approach. Then, users that spontaneously contributed are directly contacted and asked to provide additional information following a participatory approach. To demonstrate its feasibility and usefulness, we experimented the proposed paradigm for involving Twitter users in an emergency relief scenario. For each of the two real-world experiments we analyze the answer ratio to our questions, their time distribution, and responders' willingness to collaborate. Results support the adoption of hybrid crowdsensing, especially in those practical scenarios where users are emotionally involved.
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