Internet Science: 6th International Conference, INSCI 2019, Perpignan, France, December 2–5, 2019, Proceedings

This paper seeks to discuss whether and how digital collaborative sharing platforms can foster citizen engagement in urban neighbourhoods by addressing various challenges experienced by local initiatives. To that aim, we conducted a case study in the Saupstad neighbourhood of Trondheim in Norway. Our case study includes qualitative interviews conducted with volunteers and general managers of a selection of central volunteering initiatives in Saupstad where we aimed to map the current state of neighbourhood volunteerism, and identify the challenges experienced both at the individual and organizational level. We also involved stakeholders in a co-creative dialogue meeting to discuss and develop scenarios to overcome the identified challenges and foster citizen engagement in volunteering activities. Based on the empirical data we collected, we have identified challenges centralized around the interrelated themes such as ‘volunteer motivation’, ‘volunteer recruitment’, ‘effective dissemination of information’ and ‘collaboration and communication with local actors’. In this paper we discuss to what extent collaborative platforms can address these challenges and be utilized to foster citizen participation.

[1]  J. Gittins Bandit processes and dynamic allocation indices , 1979 .

[2]  P. Fischer,et al.  Civil courage: Implicit theories, related concepts, and measurement , 2007 .

[3]  Mark Levine,et al.  Identity and Emergency Intervention: How Social Group Membership and Inclusiveness of Group Boundaries Shape Helping Behavior , 2005, Personality & social psychology bulletin.

[4]  R. D. Clark,et al.  Why don't bystanders help? Because of ambiguity? , 1972 .

[5]  Bing Liu,et al.  Sentiment Analysis and Subjectivity , 2010, Handbook of Natural Language Processing.

[6]  S. Chow,et al.  Sample Size Calculations In Clinical Research , 2007 .

[7]  Karl L. Wuensch,et al.  Electronic Helping Behavior: The Virtual Presence of Others Makes a Difference , 2005 .

[8]  Bystander intervention: Group size and victim status. , 1973 .

[9]  M. Steenbergen,et al.  Measuring Political Deliberation: A Discourse Quality Index , 2003 .

[10]  Adrian C. North,et al.  Diffusion of responsibility on social networking sites , 2015, Comput. Hum. Behav..

[11]  James M. Dabbs,et al.  Sex, Group Size and Helping in Three Cities* , 1975 .

[12]  T. Postmes,et al.  Deindividuation and antinormative behavior: A meta-analysis. , 1998 .

[13]  Greg Barron,et al.  Private e-mail requests and the diffusion of responsibility , 2002, Comput. Hum. Behav..

[14]  Stefaan Verhulst Where and when AI and CI meet: exploring the intersection of artificial and collective intelligence towards the goal of innovating how we govern , 2018, AI & SOCIETY.

[15]  S. Asch Effects of Group Pressure Upon the Modification and Distortion of Judgments , 1951 .

[16]  Alfredo García Forecast Horizon for a Class of Dynamic Games , 2004 .

[17]  Robert A. Paton,et al.  Value co‐creation through collective intelligence in the public sector , 2012 .

[18]  H. Young,et al.  The Evolution of Conventions , 1993 .

[19]  JAMES SUROWIECKI,et al.  The wisdom of crowds , 2016, The Lancet.

[20]  R. Amir STOCHASTIC GAMES IN ECONOMICS AND RELATED FIELDS: AN OVERVIEW , 2001 .

[21]  Michael P. Wellman,et al.  Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm , 1998, ICML.

[22]  Fabrizio Bracco,et al.  Psychometric Properties of a Revised Version of the Ten Item Personality Inventory , 2015 .

[23]  E. Maskin,et al.  A Theory of Dynamic Oligopoly, II: Price Competition , 1985 .

[24]  Jennifer Stromer-Galley Measuring Deliberation's Content: A Coding , 2007 .

[25]  Peter Fischer,et al.  The Unresponsive Bystander: Are Bystanders More Responsive in Dangerous Emergencies? , 2006 .

[26]  C. Shapiro,et al.  Network Externalities, Competition, and Compatibility , 1985 .

[27]  P. V. Lange,et al.  Why prosocials exhibit greater cooperation than proselfs: the roles of social responsibility and reciprocity , 2001 .

[28]  Tadeusz M. Szuba,et al.  Computational Collective Intelligence , 2001, Lecture Notes in Computer Science.

[29]  A. Galeotti,et al.  The Law of the Few , 2010 .

[30]  C. Cox,et al.  Predicting Successful Responses to Emergencies: the Emergency Responsiveness Scale , 2017 .

[31]  D. Meyer,et al.  Supporting Online Material Materials and Methods Som Text Figs. S1 to S6 References Evidence for a Collective Intelligence Factor in the Performance of Human Groups , 2022 .

[32]  Giuseppe Carbone,et al.  Mimicking the collective intelligence of human groups as an optimization tool for complex problems , 2018 .

[33]  P. Markey Bystander intervention in computer-mediated communication , 2000 .

[34]  Gianluigi Viscusi,et al.  Introduction to Creating and Capturing Value Through Crowdsourcing , 2018 .

[35]  K. Williams,et al.  Many Hands Make Light the Work: The Causes and Consequences of Social Loafing , 1979 .

[36]  Rahman Haghighat,et al.  The Development of the Brief Social Desirability Scale (BSDS) , 2007 .

[37]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[38]  R. Cramer,et al.  Subject competence and minimization of the bystander effect. , 1988 .

[39]  Felipe Vilanova,et al.  Deindividuation: From Le Bon to the social identity model of deindividuation effects , 2017 .

[40]  T. Postmes,et al.  Short Communication A social identity approach to trust: Interpersonal perception, group membership and trusting behaviour , 2005 .

[41]  T. Postmes,et al.  Breaching or Building Social Boundaries? , 1998 .

[42]  W. Siemaszko,et al.  "Ludobójstwo dokonane przez nacjonalistów ukraińskich na ludności polskiej Wołynia 1939-1945", Władysław Siemaszko, Ewa Siemaszko, Warszawa 2000 : [recenzja] / D. J. , 2002 .

[43]  R. Rob,et al.  Learning, Mutation, and Long Run Equilibria in Games , 1993 .

[44]  Tadeusz Szuba,et al.  Formal and computational model of Adam Smith’s Invisible Hand , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

[45]  Robert A. Eckhoff,et al.  David against Goliath? Group size and bystander effects in virtual knowledge sharing , 2008 .

[46]  Keith B. Hall,et al.  Correlated Q-Learning , 2003, ICML.

[47]  Dorian Kodelja,et al.  Multiagent cooperation and competition with deep reinforcement learning , 2015, PloS one.

[48]  R. Mattick,et al.  Development and validation of measures of social phobia scrutiny fear and social interaction anxiety. , 1998, Behaviour research and therapy.

[49]  Sung-Shun Weng,et al.  A factor-identifying study of the user-perceived value of collective intelligence based on online social networks , 2018, Internet Res..

[50]  Ilaria Giannoccaro,et al.  Criticality triggers the emergence of collective intelligence in groups. , 2017, Physical review. E.

[51]  Mollie E. Brooks,et al.  Generalized linear mixed models: a practical guide for ecology and evolution. , 2009, Trends in ecology & evolution.

[52]  Henk Elffers,et al.  Be Aware to Care: Public Self-Awareness Leads to a Reversal of the Bystander Effect. , 2012 .

[53]  R. Schwarzer,et al.  The General Self-Efficacy Scale: Multicultural Validation Studies , 2005, The Journal of psychology.

[54]  Claudio Barbaranelli,et al.  The MTSOCS: A multidimensional sense of community scale for local communities , 2009 .

[55]  M. Leary A Brief Version of the Fear of Negative Evaluation Scale , 1983 .

[56]  Svetlana Bodrunova,et al.  Beyond Left and Right: Real-World Political Polarization in Twitter Discussions on Inter-Ethnic Conflicts , 2019, Media and Communication.

[57]  Andrew N. Christopher,et al.  Fear of Negative Evaluation Affects Helping Behavior: The Bystander Effect Revisited , 2006 .

[58]  R. Aumann Agreeing to disagree. , 1976, Nature cell biology.

[59]  V. Banyard Measurement and Correlates of Prosocial Bystander Behavior: The Case of Interpersonal Violence , 2008, Violence and Victims.

[60]  Albert Mehrabian,et al.  Relations among personality scales of aggression, violence, and empathy: Validational evidence bearing on the risk of eruptive violence scale , 1997 .

[61]  B. Latané,et al.  Bystander intervention in emergencies: diffusion of responsibility. , 1968, Journal of personality and social psychology.

[62]  R. Spears,et al.  De‐individuation and group polarization in computer‐mediated communication , 1990 .

[63]  Karl L. Wuensch,et al.  The impact of recipient list size and priority signs on electronic helping behavior , 2004, Comput. Hum. Behav..

[64]  Demis Hassabis,et al.  Mastering the game of Go without human knowledge , 2017, Nature.

[65]  Johan Bollen,et al.  Twitter mood predicts the stock market , 2010, J. Comput. Sci..

[66]  D. Reynald,et al.  Australian Internet Users and Guardianship against Cyber Abuse: An Empirical Analysis , 2014 .

[67]  Yoav Shoham,et al.  If multi-agent learning is the answer, what is the question? , 2007, Artif. Intell..

[68]  A. Woolley,et al.  Collective Intelligence and Group Performance , 2015 .

[69]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[70]  M. Heene,et al.  The bystander-effect: a meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. , 2011, Psychological bulletin.