A repository for tracking citations/references/uses of rtweet in published articles because (a) people aren’t always great about using appropriate citations for R packages, (b) Google scholar hasn’t been great at locating/tracking rtweet citations, and (c) I’d like to one day get tenure :).
62. Xu S, Zhou A (2020). “Hashtag homophily in twitter
network: Examining a controversial cause-related
marketing
campaign.” Computers in Human Behavior, 102, 87-96.
61. Zhang X, Mu L (2020). “Incorporating Online Survey
and Social Media Data into a GIS Analysis for
Measuring
Walkability.” In Geospatial Technologies for Urban Health, 133-155.
Springer.
60. Aglionby G, Davis CI, Mishra P, Caines A,
Yannakoudakis H, Rei M, Shutova E, Buttery P
(2019).
“CAMsterdam at SemEval-2019 Task 6: Neural
and graph-based feature extraction for the identification
of
offensive tweets.” In Proceedings of the 13th International Workshop on
Semantic Evaluation,
556-563.
59. Agrawal T, Singhal A (2019). “An Efficient
Knowledge-Based Text Pre-processing Approach for Twitter
and
Google+.” In International Conference on Advances in Computing and Data
Sciences, 379-389.
Springer.
58. Boot AB, Sang ETK, Dijkstra K, Zwaan RA (2019). “How
character limit affects language usage in
tweets.” Palgrave
Communications, 5(1), 76.
57. Bradley A, James RJ (2019). “How are major gambling
brands using Twitter?” International
Gambling Studies,
1-20. doi: 10.1080/14459795.2019.1606927 (URL:
https://doi.org/
10.1080/14459795.2019.1606927).
56. Burton JW, Cruz N, Hahn U (2019). “How Real is Moral
Contagion in Online Social Networks?” In
Proceedings of the
Cognitive Science Society.
55. Burton N (2019). “Exploring user sentiment towards
sponsorship and ambush marketing.” International
Journal of
Sports Marketing and Sponsorship.
54. Garcia-Rudolph A, Laxe S, Saurí J, Guitart MB (2019).
“Stroke Survivors on Twitter: Sentiment and
Topic Analysis
From a Gender Perspective.” Journal of medical Internet research,
21(8), e14077.
53. Georgakopoulos SV, Tasoulis SK, Vrahatis AG,
Plagianakos VP (2019). “Convolutional Neural Networks
for
Twitter Text Toxicity Analysis.” In INNS Big Data and Deep Learning
conference, 370-379.
Springer.
52. Gitto S, Mancuso P (2019). “Brand perceptions of
airports using social networks.” Journal of Air
Transport
Management, 75, 153 - 163. ISSN 0969-6997, doi:
10.1016/j.jairtraman.2019.01.010
(URL:
https://doi.org/10.1016/j.jairtraman.2019.01.010),
<URL:
http://www.sciencedirect.com/science/
article/pii/S0969699718303144>.
51. Gray AA (2019). Brands Take a Stand for Good: The
Effect of Brand Activism on Social Media
Engagement. Senior
Honors Thesis, University of New Hampshire, Durham.
50. Greco F, Polli A, others (2019). “Vaccines in Italy:
the emotional text mining of social media.”
RIEDS-Rivista
Italiana di Economia, Demografia e Statistica-Italian Review of
Economics, Demography
and Statistics, 73(1), 89-99.
49. Heft A (2019). “The Panama Papers investigation and
the scope and boundaries of its networked
publics:
Cross-border journalistic collaboration driving transnationally
networked public spheres.”
Journal of Applied Journalism &
Media Studies, 8(2), 191-209.
48. Hunt K, Gruszczynski M (2019). “The influence of new
and traditional media coverage on public
attention to social
movements: the case of the Dakota Access Pipeline protests.”
Information,
Communication & Society, 1-17.
47. Jones NM, Silver RC (2019). “This is not a drill:
Anxiety on Twitter following the 2018 Hawaii false
missile
alert.” American Psychologist.
46. Justice JW, Bricker BJ (2019). “Hacked: Defining the
2016 Presidential Election in the Liberal
Media.” Rhetoric
and Public Affairs, 22(3), 389-420.
45. Kearney MW (2019). “Analyzing change in network
polarization.” New Media & Society.
doi:
10.1177/1461444818822813 (URL:
https://doi.org/10.1177/1461444818822813), [Online First],
<URL:
10.1177/1461444818822813>.
44. Larsen EG, Fazekas Z (2019). “Quantitative Politics with R.” NA.
43. Li TR, Chamrajnagar A, Fong X, Rizik N, Fu F (2019).
“Sentiment-based prediction of alternative
cryptocurrency
price fluctuations using gradient boosting tree model.” Frontiers in
Physics, 7,
98. doi: 10.3389/fphy.2019.00098 (URL:
https://doi.org/10.3389/fphy.2019.00098).
42. Lutkenhaus RO, Jansz J, Bouman MP (2019). “Tailoring
in the digital era: Stimulating dialogues
on health topics in
collaboration with social media influencers.” DIGITAL HEALTH,
5,
2055207618821521. doi: 10.1177/2055207618821521 (URL:
https://doi.org/10.1177/2055207618821521).
41. Lutkenhaus RO, Jansz J, Bouman MP (2019). “Mapping
the Dutch Vaccination Debate on Twitter:
Identifying
Communities, Narratives, and Interactions.” Vaccine: X, 100019.
40. M’Bareck ML (2019). Political Speech on Twitter: A
Sentiment Analysis of Tweets and News Coverage
of Local Gun
Policy. Ph.D. thesis, University of Arkansas.
39. Noaeen M, Far BH (2019). “Social media analysis for
traffic management.” In Proceedings of the
14th
International Conference on Global Software
Engineering, 72-73. IEEE Press.
38. Prieu C (2019). “Changing Faces of Morphological
Innovation in French: Gender-Marking in Feminist
Discourse on
Twitter.” In 49th Linguistic Symposium on Romance Languages in Spring
2019.
37. Rekik A, Jamoussi S, Hamadou AB (2019). “Violent
Vocabulary Extraction Methodology: Application to
the
Radicalism Detection on Social Media.” In International Conference on
Computational Collective
Intelligence, 97-109. Springer.
36. Sansone A, Cignarelli A, Ciocca G, Pozza C, Giorgino
F, Romanelli F, Jannini EA (2019). “The
Sentiment Analysis of
Tweets as a New Tool to Measure Public Perception of Male Erectile
and
Ejaculatory Dysfunctions.” Sexual Medicine.
35. Bakar MAA, Ariff NM, Hui EX (2018). “Exploratory data
analysis of Twitter’s rhythm in Malaysia.” In
AIP Conference
Proceedings, volume 2013 number 1, 020056. AIP Publishing.
34. Bossetta M (2018). “A simulated cyberattack on
Twitter: Assessing partisan vulnerability to spear
phishing
and disinformation ahead of the 2018 U.S. midterm elections.” First
Monday, 23(12).
ISSN 13960466, doi: 10.5210/fm.v23i12.9540
(URL: https://doi.org/10.5210/fm.v23i12.9540),
<URL:
https://firstmonday.org/ojs/index.php/fm/article/view/9540>.
33. Buscema M, Ferilli G, Massini G, Zavarrone E (2018).
“Media content analysis on online hate
speech.” Positive
Messengers. <URL:
https://positivemessengers.net/images/library/pdfs/
Media_content_analysis_form_eng.pdf>.
32. Cantos Sancho A (2018). Estudio de Nuevas
Herramientas en la Respuesta del Consumidor. Ph.D.
thesis,
Universitat Politécnica De Valéncia.
31. Díez MM, Palacio V, Principe O, Gaztelumendi S
(2018). “Palabras clave en twiter de centros
meteorológicos.”
Acta de las Jornadas Científicas de la Asociación Meteorológica
Española,
1(35).
30. Doceka D (2018). “Selfies as a mental disorder,
escaped biometric database and tax optimization of
Google.”
Lupa. <URL:
https://www.lupa.cz/clanky/selfies-jako-dusevni-porucha-unikla-biometricka-
databaze-a-danove-optimalizace-googlu/>.
29. Erlandsen M (2018). “Twitter as a tool of
para-disploomacy: An exploratory cohort study based
on
Catalonia (2013-2017).” Revista Chilena de Relaciones Internacionales,
2, 211-231.
<URL:
https://rchri.cl/wp-content/uploads/2018/04/211-231.pdf>.
28. Greenhalgh SP (2018). Spaces and their social
frontiers: Using community dimensions to distinguish
between
teacher-focused hashtags on Twitter. Ph.D. thesis, Michigan State
University.
27. González F, Medina V (2018). “Shaping the public
sphere: The politics of fictional expectations in
social
media.” working paper.
26. Jann O, Schottmuller C (2018). “Breakdown of debate
and the usefulness of echo chambers: Theory
and evidence.”
working paper, <URL:
https://editorialexpress.com/cgi-bin/conference/download.cgi?
db_name=EEAESEM2018&paper_id=2395>.
25. Kearney MW (2018). Analyzing tweets about the 2016 US presidential “blunder” election. ABC-CLIO.
24. Krsová L (2018). Czech journalists on Twitter:
Analysis of social interactions of the Czech media
space.
Master’s thesis, Univerzita Karlova.
23. Ku T, Xu S, Li W, Yuan B, others (2018). “Affective
Emotional Component Analysis: Text Mining Based
on Social
Network.” OSF Preprints. doi: 10.31219/osf.io/tpuw3 (URL:
https://doi.org/10.31219/
osf.io/tpuw3).
22. Lacroix D (2018). Tweeting populist sentiment: A
study of Forum voor Democratie’s use
of emotional language on
Twitter. Ph.D. thesis, University of Amsterdam. <URL:
http://
www.scriptiesonline.uba.uva.nl/document/666363>.
21. Molyneux L, Lewis SC, Holton AE (2018). “Media work,
identity, and the motivations that shape
branding practices
among journalists: An explanatory framework.” New Media & Society,
1-20. doi:
10.1177/1461444818809392 (URL:
https://doi.org/10.1177/1461444818809392).
20. Rottigni E (2018). Fragile cities: how Venice and
Barcelona communicate their need for
sustainability. B.S.
thesis, Università Ca’Foscari Venezia.
19. Rudis B (2018). 21 recipes for mining Twitter with
rtweet. rud.is. <URL:
https://rud.is/books/21-
recipes/>.
18. Štědroňová J (2018). “Inkluzivní povaha Twitterové
komunikace politik: je Twitter skutečně
demokratizující
systém?” Univerzita Karlova, Filozofická fakulta.
17. Tasoulis SK, Vrahatis AG, Georgakopoulos SV,
Plagianakos VP (2018). “Real time sentiment change
detection
of Twitter data streams.” arXiv:1804.00482.
16. Thorson AA (2018). Social networks & price
forecasting: The case of Bitcoins. Bachelor’s
Degree,
University of Barcelona.
15. Tomohira N, Wakamatsu H (2018). “On the use of
adjectives of”different" and its distribution."
In
Proceedings of the 24th Annual Conference of the
Society of Language Processing.
14. Tsoi KK, Zhang L, Chan NB, Chan FC, Hirai HW, Meng HM
(2018). “Social media as a tool to look for
people with
dementia who become lost: Factors that matter.” In Proceedings of the
51st Hawaii
International Conference on System Sciences.
13. Tsoi KK, Chan NB, Chan FC, Zhang L, Lee AC, Meng HM
(2018). “How can we better use Twitter to find a
person who
got lost due to dementia?” npj Digital Medicine, 1(1), 14.
12. Ueda A (2018). SNS political advertisement
communication: Building relationship between voters
and
politicians in election environment in Japan. Master’s thesis, Kyoto
University. <URL: http://
hdl.handle.net/2433/229491>.
11. Unsihuay JEG (2018). “Topic modeling en datos de
Twitter: Una aplicación en el contexto político
peruano.”
XXVIII Simposio Internacional de Estadístic.
10. Wu H, Ying S (2018). “Finding Similar Users over
Multiple Attributes on the Basis of Intuitionistic
Fuzzy
Set.” Mobile Networks and Applications, 1-9.
9. Akitsune K, Suzuki T (2017). Network Analysis,
series Learning with R Data Science, 2 edition.
Kyoritsu
Shuppan.
8. Fitzgerald JD (2017). “Sentiment analysis of (you
guessed it!) Donald Trump’s tweets.” Storybench.
<URL:
http://www.storybench.org/sentiment-analysis-of-you-guessed-it-donald-trumps-tweets/>.
7. Kearney MW (2017). A network-based approach to
estimating partisanship and analyzing change in
polarization
during the 2016 general election. Ph.D. thesis, University of Kansas.
6. Lanzetta VB (2017). R data visualization recipes: A
cookbook with 65+ data visualization recipes
for smarter
decision-making. Packt Publishing Ltd.
5. Mandal JK, Dutta P, Mukhopadhyay S (2017).
Computational intelligence, communications, and
business
analytics: First international conference,
CICBA 2017, Kolkata, India, March 24-25, 2017,
Revised
Selected Papers, volume 775. Springer.
4. Sinha R, Kumar M, Goswami S (2017). “An approach to
build a database for crimes in India using
Twitter.” In
International Conference on Computational Intelligence, Communications,
and Business
Analytics, 150-160. Springer.
3. Tancoigne E (2017). “Four things Twitter tells us
about”Citizen Science" (and 1,000 things
it doesn’t)."
Citizen Sciences: Rethinking Science and Public Participation. <URL:
http://
citizensciences.net/2017/01/26/4-things-twitter-tells-us-about-citizen-science/>.
2. Valls F, Redondo E, Fonseca D, Torres-Kompen R,
Villagrasa S, Martí N (2017). “Urban data and
urban design: A
data mining approach to architecture education.” Telematics and
Informatics. doi:
10.1016/j.tele.2017.09.015 (URL:
https://doi.org/10.1016/j.tele.2017.09.015).
1. Porcu V (2016). Text mining e sentiment analysis con R. Valentina Porcu.
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