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Twitter, communication, science, dissemination, impact, public, participation, computational analysis
Álvarez-Bornstein, B., & Montesi, M. (2019). Who is interacting with researchers on Twitter? A survey in the field of Information Science. JLIS, 10(2), 87-106. https://doi.org/10.4403/jlis.it-12530
Arrabal, G., & De-Aguilera, M. (2016). Comunicar en 140 caracteres. Cómo usan Twitter los comunicadores en España. [Communicating in 140 characters. How journalists in Spain use Twitter]. Comunicar, 46, 9-17. https://doi.org/10.3916/C46-2016-01
Bauer, M.W., Allum, N., & Miller, S. (2007). What can we learn from 25 years of PUS survey research? Liberating and expanding the agenda. Public Understanding of Science, 16(1), 79-95. https://doi.org/10.1177/0963662506071287
Bauer, M.W., Shukla, R., & Allum, N. (2012). Towards cultural indicators of science with global validity. In M.W. Bauer, R. Shukla, & N. Allum (Eds.), The culture of science: How the public relates to science across the globe (pp. 1-17). Routledge. https://doi.org/10.4324/9780203813621
Becker, B.F.H., Larson, H.J., Bonhoeffer, J., Van-Mulligen, E.M., Kors, J.A., & Sturkenboom, M. (2016). Evaluation of a multinational, multilingual vaccine debate on Twitter. Vaccine, 34(50), 6166-6171. https://doi.org/10.1016/j.vaccine.2016.11.007
Blei, D.M., Ng, A.Y., & Jordan, M.I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022. https://bit.ly/2wQLaGj
Brossard, D., & Scheufele, D.A. (2013). Science, new media, and the public. Science, 339(6115), 40-41. https://doi.org/10.1126/science.1232329
Büchi, M. (2016). Microblogging as an extension of science reporting. Public Understanding of Science, 26(8), 953-968. https://doi.org/10.1177/0963662516657794
Dann, S. (2010). Twitter content classification. First Monday, 15(12). https://doi.org/10.5210/fm.v15i12.2745
Davis, R.C. (1958). The public impact of science in the mass media. Institute for Social Research, University of Michigan. https://stanford.io/2w9teGk
Dehkharghani, R., Mercan, H., Javeed, A., & Saygin, Y. (2014). Sentimental causal rule discovery from Twitter. Expert Systems with Applications, 41(10), 4950-4958. https://doi.org/10.1016/j.eswa.2014.02.024
European Commission (Ed.) (2008). Public engagement in science. Publications Office of the European Union. https://bit.ly/2uB98Vg
Kahle, K., Sharon, A.J., & Baram-Tsabari, A. (2016). Footprints of fascination: Digital traces of public engagement with particle physics on CERN's social media platforms. PLoS One, 11(5). https://doi.org/10.1371/journal.pone.0156409
Kaiser, D., Durant, J., Levenson, T., Wiehe, B., & Linett, P. (2014). The evolving culture of science engagement: an exploratory initiative. MIT & Culture Kettle. https://bit.ly/2Wjy5hG
Kapoor, K.K., Tamilmani, K., Rana, N.P., Patil, P., Dwivedi, Y.K., & Nerur, S. (2018). Advances in social media research: Past, present and future. Information Systems Frontiers, 20(3), 531-558. https://doi.org/10.1007/s10796-017-9810-y
Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a social network or a news media? In M. Rappa, & P. Jones (Eds.), Proceedings of the 19th International Conference on World Wide Web (pp. 591-600). ACM. https://doi.org/10.1145/1772690.1772751
Li, R., Crowe, J., Leifer, D., Zou, L., & Schoof, J. (2019). Beyond big data: Social media challenges and opportunities for understanding social perception of energy. Energy Research & Social Science, 56. https://doi.org/10.1016/j.erss.2019.101217
López-Pérez, L., & Olvera-Lobo, M.D. (2019). Participación digital del público en la ciencia de excelencia española: Análisis de los proyectos financiados por el European Research Council. El Profesional de la Información, 28(1), 1-10. https://doi.org/10.3145/epi.2019.ene.06
Matthes, J., & Kohring, M. (2008). The content analysis of media frames: Toward improving reliability and validity. Journal of Communication, 58(2), 258-279. https://doi.org/10.1111/j.1460-2466.2008.00384.x
Mohammadi, E., Thelwall, M., Kwasny, M., & Holmes, K.L. (2018). Academic information on Twitter: A user survey. PLoS One, 13(5). https://doi.org/10.1371/journal.pone.0197265
Moreno-Castro, C., Corell-Doménech, M., & Camano-Puig, R. (2019). Which has more influence on perception of pseudo-therapies: The media’s information, friends or acquaintances opinion, or educational background? Communication & Society, 32, 35-49. https://doi.org/10.15581/003.32.3.35-48
Murphy, J., Hill, C., & Dean, E. (2013). Social media, sociality, and survey research. In C. Hill, J. Murphy and E. Dean (Eds.), Social media, sociality, and survey research (pp. 1-33). John Wiley & Sons. https://doi.org/10.1002/9781118751534.ch1
Murphy, J., Link, M.W., Childs, J.H., Tesfaye, C.L., Dean, E., Stern, M., Pasek, J., Cohen, J., Callegaro, M., & Harwood, P. (2014). Social media in public opinion research: Executive summary of the AAPOR task force on emerging technologies in public opinion research. Public Opinion Quarterly, 78(4), 788-794. https://doi.org/doi:10.1093/poq/nfu053
Myers, S. A., Sharma, A., Gupta, P., & Lin, J. (2014). Information network or social network? the structure of the twitter follow graph. In Proceedings of the 23rd International Conference on World Wide Web (pp. 493-498). ACM. https://doi.org/10.1145/2567948.2576939
Naaman, M., Boase, J., & Lai, C.H. (2010). Is it really about me? message content in social awareness streams. In Proceedings of the 2010 ACM conference on Computer supported cooperative work (pp. 189-192). ACM. https://doi.org/10.1145/1718918.1718953
Narr, S., Luca, E.W.D., & Albayrak, S. (2011). Extracting semantic annotations from twitter. In Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval (pp. 15-16). ACM. https://doi.org/10.1145/2064713.2064723
Nisbet, M.C., & Scheufele, D.A. (2009). What's next for science communication? Promising directions and lingering distractions. American Journal of Botany, 96(10), 1767-1778. https://doi.org/10.3732/ajb.0900041
Pardo, R. (2001). La cultura científico-tecnológica de las sociedades de la modernidad tardía. Treballs de la Societat Catalana de Biologia, 51, 35-63. https://bit.ly/2T0n8B5
Pearce, W., Holmberg, K., Hellsten, I., & Nerlich, B. (2014). Climate Change on Twitter: Topics, communities and conversations about the 2013 IPCC working group 1 report. PLoS One, 9(4). https://doi.org/10.1371/journal.pone.0094785
Pérez-Rodríguez, A.V., González-Pedraz, C., & Alonso-Berrocal, J.L. (2018). Twitter como herramienta de comunicación científica en España. Principales agentes y redes de comunicación. Communication Papers, 7(13), 95-112. https://doi.org/10.33115/udg_bib/cp.v7i13.21986
Santoveña, S., & Bernal, C. (2019). Explorando la influencia del docente: Participación social en Twitter y percepción Académica. [Exploring the influence of the teacher: Social participation on Twitter and academic perception]. Comunicar, 58, 75-84. https://doi.org/10.3916/C58-2019-07
ScienceFlows (Ed.) (2019). ScienceFlows. https://bit.ly/2wGZ8dB
Shan, L., Regan, Á., De-Brún, A., Barnett, J., Van-der-Sanden, M.C.A., Wall, P., & McConnon, Á. (2014). Food crisis coverage by social and traditional media: A case study of the 2008 Irish dioxin crisis. Public Understanding of Science, 23(8), 911-928. https://doi.org/10.1177/0963662512472315
Silge, J., & Robinson, D. (2016). Tidytext: Text mining and analysis using tidy data principles in R. Journal of Open Source Software, 1(3), 37. https://doi.org/10.21105/joss.00037
Stieglitz, S., & Dang-Xuan, L. (2013). Emotions and information diffusion in social media: Sentiment of microblogs and sharing behavior. Journal of Management Information Systems, 29(4), 217-248. https://doi.org/10.2753/MIS0742-1222290408
Twitter (Ed.) (2019). Application programming interface. https://developer.twitter.com
Uren, V., & Dadzie, A.S. (2015). Public science communication on Twitter: A visual analytic approach. Aslib Journal of Information Management, 67(3), 337-355. https://doi.org/10.1108/AJIM-10-2014-0137
Veltri, G. (2013). Microblogging and nanotweets: Nanotechnology on Twitter. Public Understanding of Science, 22(7), 832-849. https://doi.org/10.1177/0963662512463510
Veltri, G., & Atanasova, D. (2015). Climate change on Twitter: Content, media ecology and information sharing behaviour. Public Understanding of Science, 26(6), 721-737. https://doi.org/10.1177/0963662515613702
Wilkinson, D., & Thelwall, M. (2012). Trending Twitter topics in English: An international comparison. Journal of the American Society for Information Science and Technology, 63(8), 1631-1646. https://doi.org/10.1002/asi.22713
Zhao, W.X. Jiang, J., Weng, J., He, J., Lim E.P., Yan, H., & Li, X. (2011). Comparing Twitter and traditional media using topic models. In P. Clough et al. (Eds.), Lecture Notes in Computer Science: Vol 6611. Advances in Information Retrieval (pp. 338-349). Springer. https://doi.org/10.1007/978-3-642-20161-5_34