Add paper

paper.bib

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+@article{twitteR2rtweet,
+  title = {Github issue #1: What differences with twitte{R}?},
+  author = {Michael W Kearney},
+  year = {2016},
+  url = {https://github.com/mkearney/rtweet/issues/1#issuecomment-492753003},
+  organization = {Github}
+}
+
+@Manual{twitteR,
+  title        = {{t}witte{R}: R based {T}witter client},
+  author       = {Gentry, Jeff},
+  organization   = {Comprehensive R Archive Network},
+  year         = 2013,
+  url          = {https://cran.r-project.org/package=twitteR}
+}
+
+@Article{tweetmodeextended,
+  title = {Giving you more characters to express yourself},
+  author = {Aliza Rosen and Ikuhiro Ihara},
+  year = {2017},
+  month = {9},
+  day = {26},
+  url = {https://blog.twitter.com/official/en_us/topics/product/2017/Giving-you-more-characters-to-express-yourself.html}
+}
+
+@Manual{rtweet,
+  title = {{r}tweet: Collecting {T}witter Data},
+  author = {Kearney, Michael W},
+  organization = {The {C}omprehensive {R} {A}rchive {N}etwork},
+  year = {2018},
+  note = {R package version 0.6.7},
+  url = {https://cran.r-project.org/package=rtweet},
+  doi = {https://doi.org/10.5281/zenodo.2528481}
+}
+
+
+
+%% ACADEMIC JOURNAL ARTICLES USING RTWEET
+
+@article{bossetta2018simulated,
+  title = {A Simulated Cyberattack on {T}witter: Assessing Partisan Vulnerability to Spear Phishing and Disinformation ahead of the 2018 {US} Midterm Elections},
+  author = {Bossetta, Michael},
+  journal = {First Monday},
+  year = {2018}
+}
+
+@article{bradley2019major,
+  title={How are major gambling brands using {T}witter?},
+  author={Bradley, Alex and James, Richard JE},
+  journal={International Gambling Studies},
+  pages={1--20},
+  year={2019},
+  publisher={Taylor \& Francis},
+  doi={https://doi.org/10.1080/14459795.2019.1606927}
+}
+
+@article{buscema2018media,
+  title = {Media content analysis on online hate speech},
+  author = {Buscema, Massimo and Ferilli, Guido and Massini, Giulia and Zavarrone, Emma},
+  journal = {Positive Messengers},
+  url = {https://positivemessengers.net/images/library/pdfs/Media_content_analysis_form_eng.pdf},
+  year = {2018}
+}
+
+
+@article{erlandsen2018twitter,
+  title = {Twitter as a tool of para-disploomacy: An exploratory cohort study based on {C}atalonia (2013-2017)},
+  author = {Erlandsen, Matthias},
+  journal = {Revista Chilena de Relaciones Internacionales},
+  volume = {2},
+  issue = {1},
+  year = {2018},
+  pages = {211-231},
+  url = {https://rchri.cl/wp-content/uploads/2018/04/211-231.pdf}
+}
+
+
+@article{gitto2019brand,
+  author = {Simone Gitto and Paolo Mancuso},
+  title = {Brand perceptions of airports using social networks},
+  journal = {Journal of Air Transport Management},
+  volume = {75},
+  pages = {153 - 163},
+  year = {2019},
+  issn = {0969-6997},
+  doi = {https://doi.org/10.1016/j.jairtraman.2019.01.010},
+  url = {http://www.sciencedirect.com/science/article/pii/S0969699718303144}
+}
+
+@article{kearney2019analyzing,
+  author = {Kearney, Michael W},
+  year   = {2019},
+  journal = {New Media \& Society},
+  title   = {Analyzing change in network polarization},
+  url     = {https://doi.org/10.1177/1461444818822813},
+  note    = {[Online First]},
+  doi     = {10.1177/1461444818822813}
+}
+
+@book{kearney2018analyzing,
+  title = {Analyzing tweets about the 2016 {US} presidential "blunder" election},
+  author = {Kearney, Michael W},
+  booktitle = {An Unprecedented Election: Media, Communication, and the Electorate in the 2016 Campaign},
+  editor = {Warner, B. R. and Bystrom, D. G. and McKinney, M. S. and Banwart, M. C.},
+  year = {2018},
+  publisher = {ABC-CLIO}
+}
+
+@article{li2018sentiment,
+  title = {Sentiment-based prediction of alternative cryptocurrency price fluctuations using gradient boosting tree model},
+  author = {Li, Tianyu Ray and Chamrajnagar, Anup S and Fong, Xander R and Rizik, Nicholas R and Fu, Feng},
+  journal = {arXiv preprint arXiv:1805.00558},
+  year = {2018}
+}
+
+
+@article{lutkenhaus2019tailoring,
+  title = {Tailoring in the digital era: Stimulating dialogues on health topics in collaboration with social media influencers},
+  author = {Lutkenhaus, Roel O and Jansz, Jeroen and Bouman, Martine PA},
+  journal = {Digital Health},
+  volume = {5},
+  pages = {1-11},
+  year = {2019},
+  doi = {10.1177/2055207618821521}
+}
+
+
+@article{lutkenhaus2019mapping,
+  title={Mapping the {D}utch Vaccination Debate on {T}witter: Identifying Communities, Narratives, and Interactions},
+  author={Lutkenhaus, Roel O and Jansz, Jeroen and Bouman, Martine PA},
+  journal={Vaccine: X},
+  pages={100019},
+  year={2019},
+  publisher={Elsevier}
+}
+
+
+@article{molyneux2018media,
+  title = {Media work, identity, and the motivations that shape branding practices among journalists: An explanatory framework},
+  author = {Molyneux, Logan and Lewis, Seth C and Holton, Avery E},
+  journal = {New Media \& Society},
+  pages = {1-20},
+  year = {2018},
+  doi = {https://doi.org/10.1177/F1461444818809392}
+}
+
+
+@article{tsoi2018can,
+  title = {How can we better use {T}witter to find a person who got lost due to dementia?},
+  author = {Tsoi, Kelvin KF and Chan, Nicholas B and Chan, Felix CH and Zhang, Lingling and Lee, Annisa CH and Meng, Helen ML},
+  journal = {npj Digital Medicine},
+  volume = {1},
+  number = {1},
+  pages = {14},
+  year = {2018},
+  publisher = {Nature Publishing Group}
+}
+
+@article{unsihuay2018topic,
+  title = {Topic modeling en datos de {T}witter: Una aplicaci{\'o}n en el contexto pol{\'\i}tico peruano},
+  author = {Unsihuay, Jes{\'u}s Eduardo Gamboa},
+  journal = {XXVIII Simposio Internacional de Estadístic},
+  year = {2018}
+}
+
+@article{valls2017urban,
+  title = {Urban data and urban design: A data mining approach to architecture education},
+  author = {Valls, Francesc and Redondo, Ernesto and Fonseca, David and Torres-Kompen, Ricardo and Villagrasa, Sergi and Mart{\'\i}, Nuria},
+  journal = {Telematics and Informatics},
+  year = {2017},
+  publisher = {Elsevier},
+  doi = {https://doi.org/10.1016/j.tele.2017.09.015}
+}
+
+@article{wu2018finding,
+  title={Finding Similar Users over Multiple Attributes on the Basis of Intuitionistic Fuzzy Set},
+  author={Wu, Haitao and Ying, Shi},
+  journal={Mobile Networks and Applications},
+  pages={1--9},
+  year={2018},
+  doi = {10.1007/s11036-018-1055-6}
+}
+
+
+
+%% MAINSTREAM PUBLICATIONS
+
+
+@article{riley2019twitter,
+  author = {Cailin Riley},
+  journal = {Futurity},
+  month = {4},
+  day = {3},
+  year = {2019},
+  title = {Does {T}witter make political polarization seem worse?},
+  url = {https://www.futurity.org/political-polarization-twitter-moderates-2025862/}
+}
+
+@article{bajak2019democrats,
+  author = {Aleszu Bajak and Floris Wu},
+  journal = {Roll Call},
+  month = {2},
+  day = {12},
+  year = {2019},
+  title = {Democrats 'went low' on {T}witter leading up to 2018},
+  url = {https://www.rollcall.com/news/lead-midterms-twitter-republicans-went-high-democrats-went-low}
+}
+
+@article{machlis2019r,
+  author = {Sharon Machlis},
+  year = {2019},
+  day = {17},
+  month = {3},
+  title = {R community blasts {D}ataCamp response to exec's 'inappropriate behavior'},
+  url = {https://www.computerworld.com/article/3389684/r-community-blasts-datacamp-response-to-execs-inappropriate-behavior.html#tk.rss_news},
+  journal = {ComputerWorld}
+}

paper.md

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+---
+title: "rtweet: Collecting and analyzing Twitter data"
+authors:
+  - name: Michael W. Kearney
+    orcid: 0000-0002-0730-4694
+    affiliation: '1'
+affiliations:
+  - name: School of Journalism, Informatics Institute, University of Missouri
+    index: '1'
+date: 13 May 2019
+bibliography: paper.bib
+tags:
+  - R
+  - twitter
+  - social media
+  - API
+---
+
+# Summary
+
+Interest in Twitter data continues to grow, but for many the task of actually
+collecting and analyzing data via Twitter APIs remains daunting. For example, in
+order to interact with Twitter's APIs users must, in addition to identifying and
+digesting the relevant information from [Twitter's developer
+documentation](https://developer.twitter.com), build/send/receive requests,
+manage rate limits, and wrangle nested and real-time response objects into
+analysis-friendly data structures. Fortunately, the ``rtweet`` package [@rtweet]
+is designed to simplify these processes, making interacting with Twitter's APIs
+more accessible to a wider range of users.
+
+Following the [announced (2016) deprecation of the ``twitteR``
+package](https://github.com/mkearney/rtweet/issues/1#issuecomment-492753003)
+[@twitteR], R users seeking to interact with Twitter APIs have been encouraged
+to use the ``rtweet`` package. Use of the up-to-date and actively-maintained
+``rtweet`` package is especially important in light of changes to Twitter's APIs
+since 2016. Most notably, one major change not reflected in the ``twitteR``
+package is the increased character limit for Twitter statuses from 140 to 280
+characters [@tweetmodeextended]). In addition to providing similar but updated
+functionality as the ``twitteR`` package for interacting with Twitter's REST
+API, the ``rtweet`` package also provides support for acessing Twitter's stream
+API.
+
+The main goals of the ``rtweet`` package are two-fold. The first goal is to make
+interacting with Twitter's APIs more approachable and streamlined for less
+computationally-experienced users. The second goal is to assist in the analysis
+of Twitter data via converting information returned by Twitter's APIs into
+tabular data structures and providing several convenience functions for common
+analytical techniques such as examining Twitter networks or the frequency of
+tweets over time. In short, although it is certainly possible for users to write
+their own Twitter API wrapper functions, the heavy-lifting done by ``rtweet`` to
+(a) streamline the building, authorizing, and sending of API requests, (b)
+wrangle deeply nested JSON data into tabular structures, and (c) provide
+convenience functions for for relevant and popular analytical techniques, make
+it a valuable contribution in the area of collecting and analyzing Twitter data.
+
+Although ``rtweet`` provides some coverage to user context-behaviors (e.g.,
+posting statuses, liking tweets, following users, etc.), the primary audience
+for the package to date has been researchers. Accordingly, ``rtweet`` has been
+featured in numerous mainstream [e.g.,
+@bajak2019democrats;@machlis2019r;@riley2019twitter] and academic publications
+[e.g.,
+@bossetta2018simulated;@bradley2019major;@buscema2018media;@erlandsen2018twitter;@gitto2019brand;@kearney2019analyzing;@kearney2018analyzing;@li2018sentiment;@lutkenhaus2019tailoring;@lutkenhaus2019mapping;@molyneux2018media;@tsoi2018can;@unsihuay2018topic;@valls2017urban;@wu2018finding].
+
+# References
+
+