References

Amores, Javier J, Carlos Arcila Calderón, and Mikolaj Stanek. 2019. “Visual Frames of Migrants and Refugees in the Main Western European Media.” Economics & Sociology 12 (3): 147–61.
Benoit, Kenneth, Kohei Watanabe, Haiyan Wang, Paul Nulty, Adam Obeng, Stefan Müller, and Akitaka Matsuo. 2018. “Quanteda: An r Package for the Quantitative Analysis of Textual Data.” Journal of Open Source Software 3 (30): 774. https://doi.org/10.21105/joss.00774.
Blei, David M, and John D Lafferty. 2006. “Dynamic Topic Models.” In Proceedings of the 23rd International Conference on Machine Learning, 113–20.
Blei, David M, Andrew Y Ng, and Michael I Jordan. 2003. “Latent Dirichlet Allocation.” Journal of Machine Learning Research 3 (Jan): 993–1022.
Blei, David, and John Lafferty. 2006. “Correlated Topic Models.” Advances in Neural Information Processing Systems 18: 147.
Blondel, Vincent D, Jean-Loup Guillaume, Renaud Lambiotte, and Etienne Lefebvre. 2008. “Fast Unfolding of Communities in Large Networks.” Journal of Statistical Mechanics: Theory and Experiment 2008 (10): P10008.
Boukes, Mark, Bob van de Velde, Theo Araujo, and Rens Vliegenthart. 2019. “What’s the Tone? Easy Doesn’t Do It: Analyzing Performance and Agreement Between Off-the-Shelf Sentiment Analysis Tools.” Communication Methods and Measures 00 (00): 1–22. https://doi.org/10.1080/19312458.2019.1671966.
Boumans, Jelle W., and Damian Trilling. 2016. “Taking stock of the toolkit: An overview of relevant autmated content analysis approaches and techniques for digital journalism scholars.” Digital Journalism 4 (1): 8–23. https://doi.org/10.1080/21670811.2015.1096598.
boyd, Danah, and Kate Crawford. 2012. “Critical questions for Big Data.” Information, Communication & Society 15 (5): 662–79. https://doi.org/10.1080/1369118X.2012.678878.
Breiman, Leo. 2001. “Statistical modeling: The two cultures.” Statistical Science 16 (3): 199–215. https://doi.org/10.1214/ss/1009213726.
Breuer, Johannes, Libby Bishop, and Katharina Kinder-Kurlanda. 2020. “The practical and ethical challenges in acquiring and sharing digital trace data: Negotiating public-private partnerships.” New Media & Society 22 (11): 2058–80. https://doi.org/10.1177/1461444820924622.
Bruns, Axel. 2019. “After the ‘APIcalypse’: social media platforms and their fight against critical scholarly research.” Information, Communication & Society 22 (11): 1544–66. https://doi.org/10.1080/1369118X.2019.1637447.
Bryman, Alan. 2012. Social Research Methods. 4th edition. New York, NY: Oxford University Press.
Burscher, Björn, Daan Odijk, Rens Vliegenthart, Maarten de Rijke, and Claes H. de Vreese. 2014. “Teaching the computer to code frames in news: Comparing two supervised machine learning approaches to frame analysis.” Communication Methods and Measures 8 (3): 190–206. https://doi.org/10.1080/19312458.2014.937527.
Cairo, Alberto. 2019. How Charts Lie. WW Norton & Company.
Cazals, Frédéric, and Chinmay Karande. 2008. “A Note on the Problem of Reporting Maximal Cliques.” Theoretical Computer Science 407 (1-3): 564–68.
Chan, Chung-hong, Joseph Bajjalieh, Loretta Auvil, Hartmut Wessler, Scott Althaus, Kasper Welbers, Wouter van Atteveldt, and Marc Jungblut. in press. “Four Best Practices for Measuring News Sentiment Using ‘Off-the-Shelf’ Dictionaries: A Large-Scale p-Hacking Experiment.” Computational Communication Research, in press.
Chang, Jonathan, Sean Gerrish, Chong Wang, Jordan L Boyd-Graber, and David M Blei. 2009. “Reading Tea Leaves: How Humans Interpret Topic Models.” In Advances in Neural Information Processing Systems, 288–96.
Chen, Lizi. 2017. “News-Processed-Dataset.” https://doi.org/10.6084/m9.figshare.5296357.v1.
Christakis, Nicholas A, and James H Fowler. 2009. Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. Little, Brown Spark.
Cioffi-Revilla, Claudio. 2014. Introduction to Computational Social Science: Principles and Applications. London, UK: Springer.
Clauset, Aaron, Mark EJ Newman, and Cristopher Moore. 2004. “Finding Community Structure in Very Large Networks.” Physical Review E 70 (6): 066111.
Codd, Edgar F. 1970. “A Relational Model of Data for Large Shared Data Banks.” Communications of the ACM 13 (6): 377–87. https://doi.org/10.1145/362384.362685.
Crawley, Michael J. 2012. The r Book. 2nd Edition. Wiley.
De Smedt, Tom, W Daelemans, and Tom De Smedt. 2012. “Pattern for Python.” The Journal of Machine Learning Research 13: 2063–67. http://dl.acm.org/citation.cfm?id=2343710.
Dietrich, Bryce J, Matthew Hayes, and DIANA Z O’BRIEN. 2019. “Pitch Perfect: Vocal Pitch and the Emotional Intensity of Congressional Speech.” American Political Science Review 113 (4): 941–62.
Eppstein, David, Maarten Löffler, and Darren Strash. 2010. “Listing All Maximal Cliques in Sparse Graphs in Near-Optimal Time.” In International Symposium on Algorithms and Computation, 403–14. Springer.
Freelon, Deen. 2018. “Computational Research in the Post-API Age.” Political Communication 35 (4): 665–68. https://doi.org/10.1080/10584609.2018.1477506.
Géron, Aurélien. 2019. Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O’Reilly Media.
Goldberg, Yoav. 2017. Neural Network Models for Natural Language Processing. Morgan & Claypool.
Gonzalez-Bailon, S., and G. Paltoglou. 2015. “Signals of Public Opinion in Online Communication: A Comparison of Methods and Data Sources.” The ANNALS of the American Academy of Political and Social Science 659 (1): 95–107. https://doi.org/10.1177/0002716215569192.
González-Bailón, Sandra. 2017. Decoding the social world: Data science and the unintended consequences of communication. Cambridge, MA: MIT.
Griffiths, Thomas L, Michael I Jordan, Joshua B Tenenbaum, and David M Blei. 2004. “Hierarchical Topic Models and the Nested Chinese Restaurant Process.” In Advances in Neural Information Processing Systems, 17–24.
Grimmer, J., and B. M. Stewart. 2013. “Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts.” Political Analysis 21 (3): 267–97. https://doi.org/10.1093/pan/mps028.
Günther, Elisabeth, Damian Trilling, and Bob van de Velde. 2018. “But How Do We Store It? Data Architecture in the Social-Scientific Research Process.” In Computational Social Science in the Age of Big Data. Concepts, Methodologies, Tools, and Applications, edited by C. M. Stuetzer, M. Welker, and M. Egger, 161–87. Herbert von Halem.
Horiuchi, Yusaku, Tadashi Komatsu, and Fumio Nakaya. 2012. “Should Candidates Smile to Win Elections? An Application of Automated Face Recognition Technology.” Political Psychology 33 (6): 925–33.
Horne, Benjamin D., William Dron, Sara Khedr, and Sibel Adali. 2018. “Sampling the News Producers: A Large News and Feature Data Set for the Study of the Complex Media Landscape.” In 12th International AAAI Conference on Web and Social Media (ICWSM), 518–27. Icwsm. http://arxiv.org/abs/1803.10124.
Hutto, Clayton J, and Eric Gilbert. 2014. “Vader: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text.” In Eighth International AAAI Conference on Weblogs and Social Media.
Jurafsky, Daniel, and James H Martin. 2009. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2nd Ed.). Prentice Hall.
Kirk, Andy. 2016. Data Visualisation: A Handbook for Data Driven Design. London, UK: SAGE.
Kitchin, Rob. 2014a. “Big Data, new epistemologies and paradigm shifts.” Big Data & Society 1 (1): 1–12. https://doi.org/10.1177/2053951714528481.
———. 2014b. The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. Sage.
Knox, Dean, and Christopher Lucas. 2021. “A Dynamic Model of Speech for the Social Sciences.” American Political Science Review 115 (2): 649–66.
Krippendorff, Klaus. 2004. Content Analysis: An Introduction to Its Methodology. 2nd ed. Thousand Oaks, CA: SAGE.
Landauer, Thomas K, Danielle S McNamara, Simon Dennis, and Walter Kintsch. 2013. Handbook of Latent Semantic Analysis. Psychology Press.
LeCun, Yann, Léon Bottou, Yoshua Bengio, and Patrick Haffner. 1998. “Gradient-Based Learning Applied to Document Recognition.” Proceedings of the IEEE 86 (11): 2278–2324.
Lin, Jimmy. 2015. “On Building Better Mousetraps and Understanding the Human Condition: Reflections on Big Data in the Social Sciences.” The ANNALS of the American Academy of Political and Social Science 659 (1): 33–47.
Maas, Andrew L., Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011. “Learning Word Vectors for Sentiment Analysis.” In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 142–50. Portland, Oregon, USA: Association for Computational Linguistics. http://www.aclweb.org/anthology/P11-1015.
Margolin, Drew B. 2019. “Computational Contributions: A Symbiotic Approach to Integrating Big, Observational Data Studies into the Communication Field.” Communication Methods and Measures 13 (4): 229–47.
Mayer-Schönberger, Viktor, and Kenneth Cukier. 2013. Big Data: A Revolution That Will Transform How We Live, Work, and Think. New York, NY: Houghton Mifflin Harcourt.
Mimno, David, Hanna Wallach, Edmund Talley, Miriam Leenders, and Andrew McCallum. 2011. “Optimizing Semantic Coherence in Topic Models.” In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, 262–72.
Moreno, Jacob Levy. 1934. Who Shall Survive? A New Approach to the Problem of Human Interrelations. Nervous; mental disease publishing co.
Newman, Mark EJ, and Michelle Girvan. 2004. “Finding and Evaluating Community Structure in Networks.” Physical Review E 69 (2): 026113.
Nothman, Joel, Hanmin Qin, and Roman Yurchak. 2018. “Stop Word Lists in Free Open-Source Software Packages.” In Proceedings of Workshop for NLP Open Source Software (NLP-OSS), 7–12.
Peng, Yilang. 2018. “Same Candidates, Different Faces: Uncovering Media Bias in Visual Portrayals of Presidential Candidates with Computer Vision.” Journal of Communication 68 (5): 920–41.
Piketty, Thomas. 2017. Capital in the Twenty-First Century. Cambridge, MA: Harvard University Press.
Puschmann, Cornelius. 2019. “An end to the wild west of social media research: a response to Axel Bruns.” Information, Communication & Society 22 (11): 1582–89. https://doi.org/10.1080/1369118X.2019.1646300.
Qi, Peng, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D. Manning. 2020. “Stanza: A Python Natural Language Processing Toolkit for Many Human Languages.” In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. https://nlp.stanford.edu/pubs/qi2020stanza.pdf.
Raghavan, Usha Nandini, Réka Albert, and Soundar Kumara. 2007. “Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks.” Physical Review E 76 (3): 036106.
Reagan, Andrew J., Christopher M. Danforth, Brian Tivnan, Jake Ryland Williams, and Peter Sheridan Dodds. 2017. “Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs.” EPJ Data Science 6 (1). https://doi.org/10.1140/epjds/s13688-017-0121-9.
Redmon, Joseph, and Ali Farhadi. 2018. “YOLOv3: An Incremental Improvement.” arXiv.
Rieder, Bernhard. 2017. “Scrutinizing an Algorithmic Technique: The Bayes Classifier as Interested Reading of Reality.” Information Communication and Society 20 (1): 100–117. https://doi.org/10.1080/1369118X.2016.1181195.
Riffe, Daniel, Stephen Lacy, Frederick Fico, and Brendan Watson. 2019. Analyzing Media Messages. Using Quantitative Content Analysis in Research. 4th edition. New York, NY: Routledge.
Riffe, Daniel, Stephen Lacy, Brendan R. Watson, and Frederick Fico. 2019. Analyzing Media Messages: Using Quantitative Content Analysis in Research. 4th ed. New York, NY: Routledge.
Roberts, Margaret E, Brandon M Stewart, Dustin Tingley, Christopher Lucas, Jetson Leder-Luis, Shana Kushner Gadarian, Bethany Albertson, and David G Rand. 2014. “Structural Topic Models for Open-Ended Survey Responses.” American Journal of Political Science 58 (4): 1064–82.
Salganik, Matthew. 2019. Bit by Bit: Social Research in the Digital Age. Princeton University Press.
Scharkow, Michael. 2011. “Thematic content analysis using supervised machine learning: An empirical evaluation using German online news.” Quality & Quantity 47 (2): 761–73. https://doi.org/10.1007/s11135-011-9545-7.
———. 2017. “Content Analysis, Automatic.” In The International Encyclopedia of Communication Research Methods, edited by Jörg Matthes, Christine S. Davis, and Robert F. Potter, 1–14. Hoboken, NJ: Wiley. https://doi.org/10.1002/9781118901731.iecrm0043.
Straka, Milan, and Jana Straková. 2017. “Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe.” In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, 88–99. Vancouver, Canada: Association for Computational Linguistics. http://www.aclweb.org/anthology/K/K17/K17-3009.pdf.
Thelwall, Mike, Kevan Buckley, and Georgios Paltoglou. 2012. “Sentiment Strength Detection for the Social Web.” Journal of the American Society for Information Science and Technology 63 (1): 163–73. https://doi.org/10.1002/asi.21662.
Trilling, Damian. 2013. “Following the news: Patterns of online and offline news consumption.” {PhD} Theses, University of Amsterdam. https://hdl.handle.net/11245/1.394551.
———. 2017. “Big Data, Analysis of.” In The International Encyclopedia of Communication Research Methods, 1–20. Hoboken, NJ, USA: John Wiley & Sons, Inc. https://doi.org/10.1002/9781118901731.iecrm0014.
Trilling, Damian, and Jeroen G. F. Jonkman. 2018. “Scaling up Content Analysis.” Communication Methods and Measures 12 (2-3): 158–74. https://doi.org/10.1080/19312458.2018.1447655.
Tufte, Edward R. 2006. Beautiful Evidence. Vol. 1. Graphics Press Cheshire, CT.
Tukey, John W. 1977. Exploratory Data Analysis. Vol. 2. Reading, Mass.
Tulkens, Stéphan, Lisa Hilte, Elise Lodewyckx, Ben Verhoeven, and Walter Daelemans. 2016. “A Dictionary-based Approach to Racism Detection in Dutch Social Media.” Proceedings of the Workshop on Text Analytics for Cybersecurity and Online Safety (TA-COS 2016), 11–17. http://www.clips.ua.ac.be/bibliography/a-dictionary-based-approach-to-racism-detection-in-dutch-social-media.
Van Atteveldt, Wouter, Anne Kroon, Felicia Loecherbach, Mickey Steijaert, Joanna Strycharz, Damian Trilling, Mariken Van der Velden, and Kasper Welbers. 2020. “Standardized Research Compendiums: Making Open and Transparent Science Fun and Easy.” Gold Coast, Australia (online due to Corona crisis).
Van Atteveldt, Wouter, Joanna Strycharz, Damian Trilling, and Kasper Welbers. 2019. “Toward Open Computational Communication Science : A Practical Road Map for Reusable Data and Code University of Amsterdam , the Netherlands.” International Journal of Communication 13: 3935–54.
Van Atteveldt, Wouter, Mariken ACG Van der Velden, and Mark Boukes. 2021. “The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms.” Communication Methods and Measures 15 (2): 121–40.
Van Atteveldt, W., T. Sheafer, S. R. Shenhav, and Y. Fogel-Dror. 2017. “Clause Analysis: Using Syntactic Information to Automatically Extract Source, Subject, and Predicate from Texts with an Application to the 2008–2009 Gaza War.” Political Analysis 25 (2): 207–22.
VanderPlas, Jake. 2016. Python Data Science Handbook: Essential Tools for Working with Data. O’Reilly.
Vermeer, Susan A. M. 2018. “A supervised machine learning method to classify Dutch-language news items.” https://doi.org/10.6084/m9.figshare.7314896.v1.
Vermeer, Susan A. M., Theo Araujo, Stefan F. Bernritter, and Guda van Noort. 2019. “Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media.” International Journal of Research in Marketing 36 (3): 492–508. https://doi.org/10.1016/j.ijresmar.2019.01.010.
Vosoughi, Soroush, Deb Roy, and Sinan Aral. 2018. “The Spread of True and False News Online.” Science 359 (6380): 1146–51.
Waldherr, Annie. 2014. “Emergence of News Waves: A Social Simulation Approach.” Journal of Communication 64 (5): 852–73. https://doi.org/10.1111/jcom.12117.
Watts, Duncan J. 2004. Six Degrees: The Science of a Connected Age. WW Norton & Company.
Wettstein, Martin. 2020. “Simulating hidden dynamics : Introducing Agent-Based Models as a tool for linkage analysis.” Computational Communication Research 2 (1): 1–33. https://doi.org/10.5117/CCR2020.1.001.WETT.
Williams, Nora Webb, Andreu Casas, and John D Wilkerson. 2020. “Images as Data for Social Science Research: An Introduction to Convolutional Neural Nets for Image Classification.” Elements in Quantitative and Computational Methods for the Social Sciences.