Wind energy: Influencing the dynamics of the public opinion formation through the retweet network

[1]  Jörg Matthes,et al.  From social media diet to public riot? Engagement with "greenfluencers" and young social media users' environmental activism , 2022, Comput. Hum. Behav..

[2]  W. Neumann,et al.  Is large-scale wind power a problem, solution, or victim? A frame analysis of the debate in Swedish media , 2022, Energy Research & Social Science.

[3]  D. Keles,et al.  Assessing technology legitimacy with topic models and sentiment analysis – The case of wind power in Germany , 2021, Technological Forecasting and Social Change.

[4]  P. Vellucci,et al.  Contrarian effect in opinion forming: Insights from Greta Thunberg phenomenon , 2021, The Journal of Mathematical Sociology.

[5]  V. Mansotra,et al.  Predicting Geolocation of Tweets: Using Combination of CNN and BiLSTM , 2021, Data Science and Engineering.

[6]  Seung-Pyo Jun,et al.  The impact of the pandemic declaration on public awareness and behavior: Focusing on COVID-19 google searches , 2021, Technological Forecasting and Social Change.

[7]  Hassan Sajjad,et al.  Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets , 2020, COLING.

[8]  M. Hekkert,et al.  Low-carbon lock-in? Exploring transformative innovation policy and offshore wind energy pathways in the Netherlands , 2020 .

[9]  Julian V. Lamy,et al.  Keep wind projects close? A case study of distance, culture, and cost in offshore and onshore wind energy siting , 2020 .

[10]  Guangqing Chi,et al.  Energy choices in Alaska: Mining people's perception and attitudes from geotagged tweets , 2020 .

[11]  Emmanuel Mogaji,et al.  Examining consumer behaviour in the UK Energy sector through the sentimental and thematic analysis of tweets , 2020 .

[12]  K. Borch,et al.  Mapping wind-power controversies on social media: Facebook as a powerful mobilizer of local resistance , 2020 .

[13]  Nathalie Dällenbach,et al.  Individual or collective? Community investment, local taxes, and the social acceptance of wind energy in Switzerland , 2019 .

[14]  Maurizio Naldi,et al.  Predicting the performance of TV series through textual and network analysis: The case of Big Bang Theory , 2019, PloS one.

[15]  Johannes Pohl,et al.  Attitudes of U.S. Wind Turbine Neighbors: Analysis of a Nationwide Survey , 2019, Energy Policy.

[16]  Asma Dhakouani,et al.  Impacts of energy efficiency policies on the integration of renewable energy , 2019, Energy Policy.

[17]  L. Zou,et al.  Beyond big data: Social media challenges and opportunities for understanding social perception of energy , 2019, Energy Research & Social Science.

[18]  Angelo Corallo,et al.  Influence parameters correlation in a Twitter event network , 2019, International Journal of Entrepreneurship and Small Business.

[19]  Yogesh Kumar Dwivedi,et al.  Polarization and acculturation in US Election 2016 outcomes – Can twitter analytics predict changes in voting preferences , 2019, Technological Forecasting and Social Change.

[20]  Rodrigo Patiño,et al.  Justice, social exclusion and indigenous opposition: A case study of wind energy development on the Isthmus of Tehuantepec, Mexico , 2019, Energy Research & Social Science.

[21]  Rafael Aleixandre-Benavent,et al.  Renewable energies: Worldwide trends in research, funding and international collaboration , 2019, Renewable Energy.

[22]  Maurizio Naldi,et al.  Interactions and Sentiment in Personal Finance Forums: An Exploratory Analysis , 2019, Inf..

[23]  Jacob Ladenburg,et al.  Where should wind energy be located? A review of preferences and visualisation approaches for wind turbine locations , 2019, Energy Research & Social Science.

[24]  Peyman Mohajerin Esfahani,et al.  Macroscopic Noisy Bounded Confidence Models With Distributed Radical Opinions , 2019, IEEE Transactions on Automatic Control.

[25]  Jorge David Gonzalez Paule,et al.  On fine-grained geolocalisation of tweets and real-time traffic incident detection , 2019, Inf. Process. Manag..

[26]  Loretta Mastroeni,et al.  Agent-Based Models for Opinion Formation: A Bibliographic Survey , 2019, IEEE Access.

[27]  Kwan Hui Lim,et al.  Geotagging tweets to landmarks using convolutional neural networks with text and posting time , 2019, IUI Companion.

[28]  Vanita Jain,et al.  Sentiment classification of twitter data belonging to renewable energy using machine learning , 2019, Journal of Information and Optimization Sciences.

[29]  Ee-Peng Lim,et al.  Fine-grained Geolocation of Tweets in Temporal Proximity , 2019, ACM Trans. Inf. Syst..

[30]  David Bidwell,et al.  Chains of trust: Energy justice, public engagement, and the first offshore wind farm in the United States , 2019, Energy Research & Social Science.

[31]  K. Borch.  Mapping value perspectives on wind power projects: The case of the danish test centre for large wind turbines , 2018, Energy Policy.

[32]  Ji-Bum Chung,et al.  Korean traditional beliefs and renewable energy transitions: Pungsu, shamanism, and the local perception of wind turbines , 2018, Energy Research & Social Science.

[33]  Nicholas A. Giudice,et al.  Seeing clearly in a virtual reality: Tourist reactions to an offshore wind project , 2018, Energy Policy.

[34]  Nina Hampl,et al.  Worldviews as predictors of wind and solar energy support in Austria: Bridging social acceptance and risk perception research , 2018 .

[35]  Meryl P. Gardner,et al.  Wind in the sails or choppy seas?: People-place relations, aesthetics and public support for the United States’ first offshore wind project , 2018, Energy Research & Social Science.

[36]  Ee-Peng Lim,et al.  Exploiting User and Venue Characteristics for Fine-Grained Tweet Geolocation , 2018, ACM Trans. Inf. Syst..

[37]  A. Jesus,et al.  Eco-Innovation in the transition to a circular economy: an analytical literature review , 2018 .

[38]  Johannes Pohl,et al.  Reconsidering barriers to wind power projects: community engagement, developer transparency and place , 2017 .

[39]  Klaus Menrad,et al.  Public participation in wind energy projects located in Germany: Which form of participation is the key to acceptance? , 2017 .

[40]  Joemon M. Jose,et al.  On Fine-Grained Geolocalisation of Tweets , 2017, ICTIR.

[41]  İlker Türker,et al.  A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links , 2017 .

[42]  Inês L. Azevedo,et al.  Perceptions of wind energy projects in two coastal Massachusetts communities , 2017 .

[43]  Joseph Rand,et al.  Thirty years of North American wind energy acceptance research: What have we learned? , 2017 .

[44]  Chad Walker,et al.  Procedural justice in Canadian wind energy development: A comparison of community-based and technocratic siting processes , 2017 .

[45]  Anahita A. N. Jami,et al.  From consultation to collaboration: A participatory framework for positive community engagement with wind energy projects in Ontario, Canada , 2017 .

[46]  Kathleen M. Carley,et al.  On Predicting Geolocation of Tweets Using Convolutional Neural Networks , 2017, SBP-BRiMS.

[47]  I. Papazu.  Nearshore Wind Resistance on Denmark’s Renewable Energy Island: Not Another NIMBY Story , 2017 .

[48]  Rong Wang,et al.  Hashtags and information virality in networked social movement: Examining hashtag co-occurrence patterns , 2016, Online Inf. Rev..

[49]  Kajsa E. Dalrymple,et al.  Politics in 140 Characters or Less: Campaign Communication, Network Interaction, and Political Participation on Twitter , 2016 .

[50]  J. Barnett,et al.  Social media in emergency management: Twitter as a tool for communicating risks to the public , 2016 .

[51]  Sufang Zhang,et al.  The effectiveness of China's wind power policy: An empirical analysis , 2016 .

[52]  Lorenzo Pareschi,et al.  Kinetic models of collective decision-making in the presence of equality bias , 2016, 1606.05674.

[53]  Vicente Carabias-Hütter,et al.  Future acceptance of wind energy production : exploring future local acceptance of wind energy production in a Swiss alpine region , 2015 .

[54]  Sheung Yin Kevin Mo,et al.  Twitter financial community sentiment and its predictive relationship to stock market movement , 2015 .

[55]  Fabián Riquelme,et al.  Measuring user influence on Twitter: A survey , 2015, Inf. Process. Manag..

[56]  Alexey S. Matveev,et al.  Opinion Dynamics in Social Networks With Hostile Camps: Consensus vs. Polarization , 2015, IEEE Transactions on Automatic Control.

[57]  Yang Liu,et al.  Who Influenced You? Predicting Retweet via Social Influence Locality , 2015, ACM Trans. Knowl. Discov. Data.

[58]  Bohumil Frantál.  Have Local Government and Public Expectations of Wind Energy Project Benefits Been Met? Implications for Repowering Schemes , 2015 .

[59]  Yvonne Rydin,et al.  Public Engagement in Decision-Making on Major Wind Energy Projects , 2015 .

[60]  Götz Walter,et al.  Determining the local acceptance of wind energy projects in Switzerland: The importance of general attitudes and project characteristics , 2014 .

[61]  Kristina Ek,et al.  Wind farms — Where and how to place them? A choice experiment approach to measure consumer preferences for characteristics of wind farm establishments in Sweden , 2014 .

[62]  Luis M. Abadie,et al.  Valuation of Wind Energy Projects: A Real Options Approach , 2014 .

[63]  Ioannis Anagnostopoulos,et al.  InfluenceTracker: Rating the impact of a Twitter account , 2014, AIAI Workshops.

[64]  Puneet Dwivedi,et al.  Diffusion of non-traditional cookstoves across western Honduras: A social network analysis , 2014 .

[65]  Chris Hankin,et al.  Ranking Twitter Influence by Combining Network Centrality and Influence Observables in an Evolutionary Model , 2013, 2013 International Conference on Signal-Image Technology & Internet-Based Systems.

[66]  William F. Gale,et al.  Harnessing social networks for promoting adoption of energy technologies in the domestic sector , 2013 .

[67]  Scott A. Hale,et al.  Where in the World Are You? Geolocation and Language Identification in Twitter* , 2013, ArXiv.

[68]  Xiaohui Yan,et al.  A biterm topic model for short texts , 2013, WWW.

[69]  Jia Yan,et al.  Mining topical influencers based on the multi-relational network in micro-blogging sites , 2013, China Communications.

[70]  D. Shipworth,et al.  The value of social networks in the diffusion of energy-efficiency innovations in UK households , 2013 .

[71]  D. Bell,et al.  Re-visiting the ‘social gap’: public opinion and relations of power in the local politics of wind energy , 2013 .

[72]  Sébastien Motsch,et al.  Heterophilious Dynamics Enhances Consensus , 2013, SIAM Rev..

[73]  Alessandro Vespignani,et al.  The Twitter of Babel: Mapping World Languages through Microblogging Platforms , 2012, PloS one.

[74]  W. Kempton,et al.  Public acceptance of offshore wind power: does perceived fairness of process matter? , 2012 .

[75]  Geraint Ellis,et al.  Large‐scale wind deployment, social acceptance , 2012 .

[76]  Benjamin K. Sovacool,et al.  Conceptualizing the acceptance of wind and solar electricity , 2012 .

[77]  Michael C. Slattery,et al.  The predominance of economic development in the support for large-scale wind farms in the U.S. Great Plains , 2012 .

[78]  L. Edelstein-Keshet,et al.  Role of social interactions in dynamic patterns of resource patches and forager aggregation , 2012, Proceedings of the National Academy of Sciences.

[79]  Dimitris Al. Katsaprakakis,et al.  A review of the environmental and human impacts from wind parks. A case study for the Prefecture of Lasithi, Crete , 2012 .

[80]  Xiaojing Sun,et al.  The current state of offshore wind energy technology development , 2012 .

[81]  Les Carr,et al.  Identifying communicator roles in twitter , 2012, WWW.

[82]  Marián Simko,et al.  Leveraging Microblogs for Resource Ranking , 2012, SOFSEM.

[83]  Stefan Stieglitz,et al.  Political Communication and Influence through Microblogging--An Empirical Analysis of Sentiment in Twitter Messages and Retweet Behavior , 2012, 2012 45th Hawaii International Conference on System Sciences.

[84]  Tony White,et al.  Modelling Influence in a Social Network: Metrics and Evaluation , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[85]  Isabel Anger,et al.  Measuring influence on Twitter , 2011, i-KNOW '11.

[86]  Duncan J. Watts,et al.  Everyone's an influencer: quantifying influence on twitter , 2011, WSDM '11.

[87]  Scott Counts,et al.  Identifying topical authorities in microblogs , 2011, WSDM '11.

[88]  Shyhtsun Felix Wu,et al.  Measuring message propagation and social influence on Twitter.com , 2010, Int. J. Commun. Networks Distributed Syst..

[89]  Mhairi Aitken,et al.  Wind power and community benefits: Challenges and opportunities , 2010 .

[90]  I. Couzin,et al.  Social interactions, information use, and the evolution of collective migration , 2010, Proceedings of the National Academy of Sciences.

[91]  Daniel M. Romero,et al.  Influence and passivity in social media , 2010, ECML/PKDD.

[92]  Christopher R. Jones,et al.  Understanding 'local' opposition to wind development in the UK: How big is a backyard? , 2010 .

[93]  Krishna P. Gummadi,et al.  Measuring User Influence in Twitter: The Million Follower Fallacy , 2010, ICWSM.

[94]  M. Slattery,et al.  Public attitudes of wind energy in Texas: Local communities in close proximity to wind farms and their effect on decision-making , 2010 .

[95]  Charles R. Warren,et al.  Does community ownership affect public attitudes to wind energy? A case study from south-west Scotland , 2010 .

[96]  Jacob Ladenburg,et al.  Attitudes towards offshore wind farms--The role of beach visits on attitude and demographic and attitude relations , 2010 .

[97]  Stefania Bandini,et al.  Agent Based Modeling and Simulation: An Informatics Perspective , 2009, J. Artif. Soc. Soc. Simul..

[98]  Janet Stephenson,et al.  Public perceptions of wind energy developments: Case studies from New Zealand , 2009 .

[99]  J. Martínez-Alier,et al.  The Politics of Landscape Value: A Case Study of Wind Farm Conflict in Rural Catalonia , 2009 .

[100]  J. Stephens,et al.  Wind Energy in US Media: A Comparative State-Level Analysis of a Critical Climate Change Mitigation Technology , 2009 .

[101]  Jacob Ladenburg,et al.  PREFERENCES OF COASTAL ZONE USER GROUPS REGARDING THE SITING OF OFFSHORE WIND FARMS , 2009 .

[102]  Andreas Kontoleon,et al.  Assessing the determinants of local acceptability of wind-farm investment: A choice experiment in the Greek Aegean Islands , 2009 .

[103]  Jacob Ladenburg,et al.  Visual impact assessment of offshore wind farms and prior experience , 2009 .

[104]  Jeremy Firestone,et al.  Public acceptance of offshore wind power projects in the USA , 2009 .

[105]  Guillaume Moreau,et al.  An immersive path-based study of wind turbines' landscape: A French case in Plouguin , 2009 .

[106]  Edgar G. Hertwich,et al.  Life cycle assessment of a floating offshore wind turbine , 2009 .

[107]  Maria Johansson,et al.  Intention to respond to local wind turbines: the role of attitudes and visual perception , 2007 .

[108]  Maarten Wolsink,et al.  Wind power implementation: The nature of public attitudes: Equity and fairness instead of ‘backyard motives’ , 2007 .

[109]  D. Horst.  NIMBY or not? Exploring the relevance of location and the politics of voiced opinions in renewable energy siting controversies , 2007 .

[110]  Alain Nadaï,et al.  “Planning”, “siting” and the local acceptance of wind power: Some lessons from the French case , 2007 .

[111]  C. Gross,et al.  Community perspectives of wind energy in Australia: The application of a justice and community fairness framework to increase social acceptance , 2007 .

[112]  Ian D. Bishop,et al.  Visual assessment of off-shore wind turbines: The influence of distance, contrast, movement and social variables , 2007 .

[113]  W. Kempton,et al.  Public opinion about large offshore wind power: Underlying factors , 2007 .

[114]  Jure Leskovec,et al.  Patterns of Influence in a Recommendation Network , 2006, PAKDD.

[115]  Kristina Ek.  Public and private attitudes towards “green” electricity: the case of Swedish wind power , 2005 .

[116]  D. Bell,et al.  The ‘Social Gap’ in Wind Farm Siting Decisions: Explanations and Policy Responses , 2005 .

[117]  David Toke,et al.  Explaining wind power planning outcomes:: some findings from a study in England and Wales , 2005 .

[118]  Jon Kleinberg,et al.  Maximizing the spread of influence through a social network , 2003, KDD '03.

[119]  David Toke,et al.  Wind Power in UK and Denmark: Can Rational Choice Help Explain Different Outcomes? , 2002 .

[120]  Atul K. Jain,et al.  Stability: Energy for a Greenhouse Planet Advanced Technology Paths to Global Climate , 2008 .

[121]  Maarten Wolsink,et al.  Wind power and the NIMBY-myth: institutional capacity and the limited significance of public support , 2000 .

[122]  T. Vicsek,et al.  Collective Motion , 1999, physics/9902023.

[123]  F. Liébana-Cabanillas,et al.  A mixed analysis of perceptions of electric and hybrid vehicles , 2020 .

[124]  David Rudolph,et al.  (Dis)Embedding the Wind – on People-Climate Reconciliation in Danish Wind Power Planning , 2019 .

[125]  Loretta Mastroeni,et al.  Opinion Dynamics in Multi-Agent Systems Under Proportional Updating and Any-to-Any Influence , 2019, AIRO Springer Series.

[126]  Johannes Pohl,et al.  Monitoring annoyance and stress effects of wind turbines on nearby residents: A comparison of U.S. and European samples. , 2019, Environment international.

[127]  El Habib Nfaoui,et al.  Using Tweets Embeddings For Hashtag Recommendation in Twitter , 2018 .

[128]  Fausto Pedro García Márquez,et al.  Wind Energy Power Prospective , 2018 .

[129]  Johannes Pohl,et al.  Understanding stress effects of wind turbine noise – The integrated approach , 2018 .

[130]  B. Slee.  Is there a case for community-based equity participation in Scottish on-shore wind energy production? Gaps in evidence and research needs , 2015 .

[131]  Lin Wang,et al.  Distributed Attitude Control of Multi-Agent Formations , 2011 .

[132]  Thomas R. Allen,et al.  Wind turbines and coastal recreation demand , 2010 .

[133]  Jacob Ladenburg,et al.  Attitudes towards on-land and offshore wind power development in Denmark; choice of development strategy , 2008 .