Climate Change on Twitter: Topics, Communities and Conversations about the 2013 IPCC Working Group 1 Report
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{"title"=>"Climate change on twitter: Topics, communities and conversations about the 2013 IPCC Working Group 1 report", "type"=>"journal", "authors"=>[{"first_name"=>"Warren", "last_name"=>"Pearce", "scopus_author_id"=>"56135759600"}, {"first_name"=>"Kim", "last_name"=>"Holmberg", "scopus_author_id"=>"25632561700"}, {"first_name"=>"Iina", "last_name"=>"Hellsten", "scopus_author_id"=>"8852059600"}, {"first_name"=>"Brigitte", "last_name"=>"Nerlich", "scopus_author_id"=>"6603918577"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"372971525", "sgr"=>"84899584492", "issn"=>"19326203", "pmid"=>"24718388", "scopus"=>"2-s2.0-84899584492", "doi"=>"10.1371/journal.pone.0094785", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"8b0f7e2c-327c-31ff-b22c-40458663af5a", "abstract"=>"In September 2013 the Intergovernmental Panel on Climate Change published its Working Group 1 report, the first comprehensive assessment of physical climate science in six years, constituting a critical event in the societal debate about climate change. This paper analyses the nature of this debate in one public forum: Twitter. Using statistical methods, tweets were analyzed to discover the hashtags used when people tweeted about the IPCC report, and how Twitter users formed communities around their conversational connections. In short, the paper presents the topics and tweeters at this particular moment in the climate debate. The most used hashtags related to themes of science, geographical location and social issues connected to climate change. Particularly noteworthy were tweets connected to Australian politics, US politics, geoengineering and fracking. Three communities of Twitter users were identified. Researcher coding of Twitter users showed how these varied according to geographical location and whether users were supportive, unsupportive or neutral in their tweets about the IPCC. Overall, users were most likely to converse with users holding similar views. However, qualitative analysis suggested the emergence of a community of Twitter users, predominantly based in the UK, where greater interaction between contrasting views took place. This analysis also illustrated the presence of a campaign by the non-governmental organization Avaaz, aimed at increasing media coverage of the IPCC report.", "link"=>"http://www.mendeley.com/research/climate-change-twitter-topics-communities-conversations-about-2013-ipcc-working-group-1-report", "reader_count"=>120, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>4, "Librarian"=>4, "Student > Doctoral Student"=>5, "Researcher"=>23, "Student > Ph. D. Student"=>36, "Student > Postgraduate"=>3, "Student > Master"=>24, "Other"=>3, "Student > Bachelor"=>12, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>4, "Librarian"=>4, "Student > Doctoral Student"=>5, "Researcher"=>23, "Student > Ph. D. Student"=>36, "Student > Postgraduate"=>3, "Student > Master"=>24, "Other"=>3, "Student > Bachelor"=>12, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Agricultural and Biological Sciences"=>9, "Arts and Humanities"=>3, "Philosophy"=>1, "Business, Management and Accounting"=>1, "Chemistry"=>3, "Computer Science"=>15, "Earth and Planetary Sciences"=>7, "Economics, Econometrics and Finance"=>1, "Energy"=>2, "Engineering"=>2, "Environmental Science"=>14, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>4, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Psychology"=>2, "Social Sciences"=>46, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Social Sciences"=>{"Social Sciences"=>46}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>2}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>14}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>3}, "Engineering"=>{"Engineering"=>2}, "Chemistry"=>{"Chemistry"=>3}, "Energy"=>{"Energy"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>7}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>15}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Linguistics"=>{"Linguistics"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Netherlands"=>2, "United States"=>1, "United Kingdom"=>5, "Ghana"=>1, "Australia"=>2, "Germany"=>1, "Spain"=>1}, "group_count"=>9}

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/1457680"], "description"=>"<p>Most frequently used hashtags associated with Australia.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "hashtags"], "article_id"=>993549, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.t004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Most_frequently_used_hashtags_associated_with_Australia_/993549", "title"=>"Most frequently used hashtags associated with Australia.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457674"], "description"=>"<p>Example tweets from each category of Twitter user.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "tweets", "twitter"], "article_id"=>993543, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.t001", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_tweets_from_each_category_of_Twitter_user_/993543", "title"=>"Example tweets from each category of Twitter user.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457650"], "description"=>"<p>Shows how many times different usernames were mentioned in the collected tweets. The data is presented on a logaritmic scale and it clearly shows how skewed the distribution of usernames mentioned is. Few usernames were mentioned many times, while many usernames were mentioned only a few times.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "tweets", "username"], "article_id"=>993519, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.g002", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Number_of_tweets_in_which_a_username_was_mentioned_logarithmic_scale_/993519", "title"=>"Number of tweets in which a username was mentioned (logarithmic scale).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457681"], "description"=>"1<p>Values above the mean are shown in italics.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "twitter", "users", "tweet"], "article_id"=>993550, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.t007", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Categorization_of_Twitter_users_by_tweet_content_and_profile_information_1_/993550", "title"=>"Categorization of Twitter users by tweet content and profile information.<sup>1</sup>", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457677"], "description"=>"<p>Twitter users with ten or more conversational connections, coded by attitude to IPCC.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "users", "conversational", "coded"], "article_id"=>993547, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.t002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Twitter_users_with_ten_or_more_conversational_connections_coded_by_attitude_to_IPCC_/993547", "title"=>"Twitter users with ten or more conversational connections, coded by attitude to IPCC.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457659"], "description"=>"<p>Each node represents a Twitter user. Size of nodes is correlated with that user's number of conversational connections. Detected communities are differentiated by color. Colors were selected randomly and should not be associated with political stance. Thickness of the edges reflects the number of conversational connections between the two usernames connected by the edge. Proximity between the nodes reflects local closeness, as nodes with more connections to each other than to the other nodes in the graph are clustered closer to each other.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "communities", "twitter", "users", "conversational", "connections", "modularity"], "article_id"=>993528, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.g003", "stats"=>{"downloads"=>9, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Detecting_three_communities_of_Twitter_users_from_conversational_connections_only_resolution_1_9_modularity_0_422_modularity_with_resolution_1_104_/993528", "title"=>"Detecting three communities of Twitter users from conversational connections only (resolution: 1.9, modularity: 0.422, modularity with resolution: 1.104).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457672"], "description"=>"<p>Conversational connections between different categories of Twitter users.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "connections", "categories", "twitter"], "article_id"=>993541, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.t008", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Conversational_connections_between_different_categories_of_Twitter_users_/993541", "title"=>"Conversational connections between different categories of Twitter users.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457682"], "description"=>"<p>Hashtags associated with social aspects of climate change.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "aspects"], "article_id"=>993551, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.t006", "stats"=>{"downloads"=>9, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hashtags_associated_with_social_aspects_of_climate_change_/993551", "title"=>"Hashtags associated with social aspects of climate change.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-09 03:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1457667"], "description"=>"<p>Twitter users were manually coded according to the content of their tweets and Twitter biography within the population of tweets analyzed. Each node represents a Twitter user. Size of nodes is correlated with that user's number of conversational connections. Climate change unsupportives, purple; climate change supportive, red; climate change neutral, green; did not tweet, light blue. Colors were selected randomly and should not be associated with political stance.</p>", "links"=>[], "tags"=>["Information technology", "text mining", "Network Analysis", "social networks", "Atmospheric science", "Climatology", "climate change", "Political science", "Public opinion", "Sociology", "communications", "Media studies", "social policy", "Social research", "Sociology of knowledge", "communities", "conversational", "connections", "coding", "views"], "article_id"=>993537, "categories"=>["Science Policy"], "users"=>["Warren Pearce", "Kim Holmberg", "Iina Hellsten", "Brigitte Nerlich"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0094785.g004", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Detecting_communities_from_conversational_connections_with_additional_coding_by_views_on_climate_change_/993537", "title"=>"Detecting communities from conversational connections with additional coding by views on climate change.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-09 03:43:31"}

PMC Usage Stats | Further Information

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Relative Metric

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