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.
Arcila Calderón, Carlos, Félix Ortega Mohedano, Mateo Álvarez, and
Miguel Vicente Mariño. 2019. “Distributed Supervised Sentiment
Analysis of Tweets: Integrating Machine Learning and Streaming Analytics
for Big Data Challenges in Communication and Audience Research.”
Empiria: Revista de Metodologı́a de Ciencias
Sociales, no. 42: 113–36.
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.
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.