Michele Osella

Policy making 2.0: From theory to practice

Abstract Government agencies are gradually moving from simpler towards more sophisticated and complex practices of social media use, which are characterized by important innovations at the technological, political and organizational level. This paper intends to provide two contributions to the current discourse about such advanced approaches to social media exploitation. The first is of practical nature and has to do with assessing the potential and the challenges of a centralized cross-platform approach to social media by government agencies in their policy making processes. The second contribution is of theoretical nature and consists in the development of a multi-dimensional framework for an integrated evaluation of such advanced practices of social media exploitation in public policy making from technological, political and organizational perspectives, drawing from theoretical constructs from different domains. The proposed framework is applied for the evaluation of a pilot consultation campaign conducted in Italy using multiple social media and concerning the large scale application of a telemedicine program.

Analyzing the Centralised Use of Multiple Social Media by Government from Innovations Diffusion Theory Perspective

Governments have started increasingly using web 2.0 social media as a new channel of interaction with citizens in various phases of public policies lifecycle. In this direction they have started moving from simpler forms of exploitation of these strong bi-directional communication channels to more complex and sophisticated ones. These attempts constitute important innovations for government agencies, so it is necessary to analyse them from this perspective as well. This paper analyzes an advanced form of centralised use of multiple social media by government agencies from this perspective, using the well established Diffusion of Innovations Theory of Rogers. It is based on a pilot application of the above approach for conducting a consultation campaign in multiple social media concerning the large scale application of a telemedicine program of the Piedmont Regional Government, Italy. It has been concluded that this approach has the fundamental preconditions for a wide diffusion (relative advantage, compatibility with existing values and processes, reasonable complexity, trialability and observability), at least in government organizations having a tradition of bi-directional communication with citizens in all phases of policy making, and also some experience in using social media for this purpose.

Policy intelligence in the era of social computing: towards a cross-policy decision support system

The paper presents a policy analysis framework developed through a process of interdisciplinary integration as well as through a process of end users needs elicitation. The proposed framework constitutes the theoretical foundation for the Decision Support Component of a technological platform bringing together Social Media and System Dynamics simulation developed within the PADGETS project. The main novelties introduced have to do with the possibility to provide decision makers with a set of concise, fresh and relevant data in a cost effective and easily understandable way.

Toward a Methodological Approach to Assess Public Value in Smart Cities

This chapter proposes a novel framework aimed at measuring performances of smart cities. The methodological approach underlying the framework has its roots in an in-depth analysis of the smart city paradigm conducted from the perspective of urban governance. In this context, the notion of public value is seen as a backdrop for exploring the various ways in which a value for society can be created in a smart city. With this respect, a multidisciplinary synthesis of various strands of literature related to smart cities paves the way to the conceptualization of a framework meant to evaluate the “smartness” of a city through the lenses of economic, social, and environmental performances, in line with the “triple sustainability” principle. This vision is subsequently operationalized by means of a harmonized set of key performance indicators (KPIs) that can be grouped into two categories (called “core” and “ancillary”): whilst “core” indicators are identified with the intent to allow international comparability and to help policy makers in benchmarking their city on a global scale, and “ancillary” indicators are crafted considering the peculiarities of the city local context. Finally, the Italian city of Turin is used as a case study for testing the proposed assessment tool.

Fast and Effective Decision Support for Crisis Management by the Analysis of People’s Reactions Collected from Twitter

The impact of human behavior during a crisis is a crucial factor that should always be taken into account by emergency managers. An early estimation of people’s reaction can be performed through information posted on social networks. This paper proposes a platform for the extraction of real time information about an ongoing crisis from social networks, to understand the main concerns issued by users involved in the crisis. Such information is combined with other contextual data, in order to estimate the impacts of different alternative actions that can be undertaken by decision makers.

Making Sense of Governmental Activities Over Social Media: A Data-Driven Approach

Although social media attracted significant interest from governments throughout the globe, the challenge of a successful exploitation of big social data to gain valuable insights in the decision making process is still unmet. This paper aims to provide policy makers with hints and actionable guidelines for a data-driven analysis of the social accounts they manage. To this aim, we firstly propose a three-dimensional modular framework to structure the analysis; then, the logical steps required within this framework for meaningfully process big social data are detailed by suggesting text mining techniques useful for the analysis. The proposed data-driven approach could lead public administrators to a better understanding of their use of social accounts and to measure the community engagement around some topics of interest. Findings can constitute fresh insights from which public policy makers may draw for enhancing the community involvement and for becoming far more reactive to the citizenry’s needs.

Translational Models for Item Recommendation.

Translational models have proven to be accurate and efficient at learning entity and relation representations from knowledge graphs for machine learning tasks such as knowledge graph completion. In the past years, knowledge graphs have shown to be beneficial for recommender systems, efficiently addressing paramount issues such as new items and data sparsity. In this paper, we show that the item recommendation problem can be seen as a specific case of knowledge graph completion problem, where the “feedback” property, which connects users to items that they like, has to be predicted. We empirically compare a set of state-of-the-art knowledge graph embeddings algorithms on the task of item recommendation on the Movielens 1M and on the LibraryThing dataset. The results show that translational models outperform typical baseline approaches based on collaborative filtering and popularity and that the dimension of the embedding vector influences the accuracy of the recommendations.

Knowledge Graph Embeddings with node2vec for Item Recommendation

In the past years, knowledge graphs have proven to be beneficial for recommender systems, efficiently addressing paramount issues such as new items and data sparsity. Graph embeddings algorithms have shown to be able to automatically learn high quality feature vectors from graph structures, enabling vector-based measures of node relatedness. In this paper, we show how node2vec can be used to generate item recommendations by learning knowledge graph embeddings. We apply node2vec on a knowledge graph built from the MovieLens 1M dataset and DBpedia and use the node relatedness to generate item recommendations. The results show that node2vec consistently outperforms a set of collaborative filtering baselines on an array of relevant metrics.

Assessing the Impacts of Electric Vehicles Uptake: A System Dynamics Approach

The shift from conventional cars to Electric Vehicles (EVs) may significantly improve air quality and consequently public health, especially if electricity is powered by renewable energy. This paper describes a System Dynamics model to estimate the environmental health impacts of alternative market scenarios for EVs diffusion in Piedmont (Italy). The scenarios account for: (a) different market shares of Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs), and (b) different trends of EVs uptake, in accordance with official electric mobility studies. The causal relationships among the variables of this complex system generate a positive feedback loop, involving: (1) EVs uptake, (2) pollutants concentration, (3) hospital admissions, and (4) public health savings. The simulation model results in an ex-ante impact evaluation tool, which is able to perform what-if analyses of different electric mobility scenarios and to compare their 2030 projections versus a reference scenario, thus allowing a counterfactual analysis able to isolate the impacts due solely to specific actions. This study has important policy implications, since the proposed model: (a) provides an integrated and comprehensive framework that allows to account for all the three dimensions of sustainability (economic, environmental, social), (b) gives ex-ante estimates of environmental health impacts of EVs uptake according to different scenarios, and quantifies the savings derived by the reduction of public health spending, converting them in monetary incentives for EVs purchase, (c) proposes recommendations for the definition of Sustainable Urban Mobility Plans of a smart city.

Smart City Governance for Sustainable Public Value Generation

Thispositionpaperbelongstoaseriesofcontributionsonsustainablepublicvaluegenerationin urbanareas.Thearticlelooksathowthecomplextransitionprocesscitieswillbeexperiencingin thecomingdecadesmaybegoverned.Inparticular,thediscussioninvestigatestheroleplayedby InformationandCommunicationTechnologies(ICTs)aswellashowtheintelligenceofsmartcities maybeorientedtowardsthegenerationofsustainablepublicvalue.Thetopicisanalysedfromavalueorientedperspectiveandinthelightofalmosttwodecadesoftechnology-driveninnovationinboth theprivateandthepublicsector.Twoconceptualframeworksareproposed.Thefirstoneidentifies themaincontributionsofferedbyICTs,namely:theenablementofnewproduction,distributionand governanceprocesses;thetransformationoforganizationalandinstitutionalarrangements;andthe informationofindividualchoicesandbehaviours.Thesecondonehighlightsthetrade-offstobe managedandtheprinciplestobeappliedforturningcityintelligenceintosustainabledevelopment. KeywoRDS Conceptual Framework, Governance, ICT, Public Value, Smart City, Sustainability