From d5a2c8db83a2559bd4a7ffe47bc6e7a3df3265ef Mon Sep 17 00:00:00 2001 From: mkearney Date: Thu, 16 May 2019 12:35:56 -0500 Subject: [PATCH] Add paper --- paper.bib | 217 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ paper.md | 66 +++++++++++++++++ 2 files changed, 283 insertions(+) create mode 100644 paper.bib create mode 100644 paper.md diff --git a/paper.bib b/paper.bib new file mode 100644 index 00000000..ead9e66b --- /dev/null +++ b/paper.bib @@ -0,0 +1,217 @@ +@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} +} diff --git a/paper.md b/paper.md new file mode 100644 index 00000000..d5a52e97 --- /dev/null +++ b/paper.md @@ -0,0 +1,66 @@ +--- +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 + +