CV_JohannesGruber.bib

@book{gruberthesis.2021,
	title = {Troublemakers in the Streets? A Framing Analysis of Newspaper Coverage of Protests in the UK 1992-2017},
	author = {\textbf{Gruber, Johannes B.}},
	year = {2021},
	doi = {10.5525/gla.thesis.82346},
	url = {https://doi.org/10.5525/gla.thesis.82346}
}


@article{GruberTroublemakers2022,
	title = {{T}roublemakers in the {S}treets? {A} {F}raming {A}nalysis of {N}ewspaper {C}overage of {P}rotests in the {UK} 1992-2017},
	author = {\textbf{Gruber, Johannes B.}},
	volume = {28},
  number = {2},
  pages = {414-433},
  year = {2023},
  journal = {The International Journal of Press/Politics},
  doi = {10.1177/19401612221102058},
	url = {https://doi.org/10.1177/19401612221102058}
}


@package{LexisNexisTools,
title = {{L}exis{N}exis{T}ools. {A}n {R} package for working with newspaper data from '{LexisNexis}'},
	author = {\textbf{Gruber, Johannes B.}},
  year = {2024},
  url = {https://github.com/JBGruber/LexisNexisTools},
  note = {R package version 1.0.0},
  downloads = {Cranlogs download count: 45,065},
}


@package{rDNA.2019,
  title = {{rDNA. A Package to Control Discourse Network Analyzer from R}},
  author = {Philip Leifeld and \textbf{Gruber, Johannes B.} and Tim Henrichsen},
  year = {2019},
  note = {R package version 2.1.18},
  organization = {University of Glasgow, School of Social and Political Sciences},
  address = {Glasgow},
  url = {http://www.philipleifeld.com},
}


@package{rwhatsapp,
  title = {rwhatsapp. An {R} package for working with {W}hats{A}pp data},
	author = {\textbf{Gruber, Johannes B.}},
  year = {2022},
  url = {https://github.com/JBGruber/rwhatsapp},
  note = {R package version 0.2.4},
  downloads = {Cranlogs download count: 34,846},
}


@package{paperboy,
  title = {paperboy. A comprehensive collection of news media scrapers},
  author = {\textbf{Gruber, Johannes B.}},
  year = {2023},
  url = {https://github.com/JBGruber/paperboy},
  note = {R package version 0.0.5.9000},
}

  
@package{traktok,
  title  = "traktok. Getting TikTok data through the official and unofficial APIs",
  author = {\textbf{Gruber, Johannes B.}},
  year = {2023},
  url = {https://github.com/JBGruber/traktok},
  note = {R package version 0.0.4.9000},
}


@Manual{Leifeld.2018,
    title = {{D}iscourse {N}etwork {A}nalyzer Manual},
    author = {Philip Leifeld and \textbf{Gruber, Johannes B.} and Felix Rolf Bossner},
    year = {2018},
    doi = {10.2307/20072882},
    url = {https://github.com/leifeld/dna/releases/download/v2.0-beta.24/dna-manual.pdf},
}

@package{cookiemonster,
  title = {{cookiemonster}: Your Friendly Solution to Managing Browser Cookies in {R}},
  author = {\textbf{Gruber, Johannes B.}},
  year = {2023},
  url = {https://github.com/JBGruber/cookiemonster},
  downloads = {Cranlogs download count: 3,224},
  note = {R package version 0.0.3}
} 


@article{Langerwindrush.2020,
	title = {Political {A}genda {S}etting in the {H}ybrid {M}edia {S}ystem. {W}hy {L}egacy {M}edia {S}till {M}atter a {G}reat {D}eal},
	author = {Ana Inés Langer and \textbf{Gruber, Johannes B.}},
	journal = {The International Journal of Press/Politics},
	volume = {26},
  number = {2},
  pages = {313-340},
  year = {2021},
	doi = {10.1177/1940161220925023},
	url = {https://journals.sagepub.com/doi/10.1177/1940161220925023}
}


@inproceedings{qtele2022,
    title = {Conspiracy Narratives in the Protest Movement Against {COVID}-19 Restrictions in {G}ermany. A Long-term Content Analysis of Telegram Chat Groups},
    author = {Weigand, Manuel and Weber, Maximilian and \textbf{Gruber, Johannes B.}},
    booktitle = {Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS)},
    month = {nov},
    year = {2022},
    address = {Abu Dhabi, UAE},
    publisher = {Association for Computational Linguistics},
    url = {https://aclanthology.org/2022.nlpcss-1.8},
    pages = {52--58},
    abstract = {From the start of the COVID-19 pandemic in Germany, different groups have been protesting measures implemented by different government bodies in Germany to control the pandemic. It was widely claimed that many of the offline and online protests were driven by conspiracy narratives disseminated through groups and channels on the messenger app Telegram. We investigate this claim by measuring the frequency of conspiracy narratives in messages from open Telegram chat groups of the Querdenken movement, set up to organize protests against COVID-19 restrictions in Germany. We furthermore explore the content of these messages using topic modelling. To this end, we collected 822k text messages sent between April 2020 and May 2022 in 34 chat groups. By fine-tuning a Distilbert model, using self-annotated data, we find that 8.24{\%} of the sent messages contain signs of conspiracy narratives. This number is not static, however, as the share of conspiracy messages grew while the overall number of messages shows a downward trend since its peak at the end of 2020. We further find a mix of known conspiracy narratives make up the topics in our topic model. Our findings suggest that the Querdenken movement is getting smaller over time, but its remaining members focus even more on conspiracy narratives.},
}


@package{amcat4r,
    title = {amcat4r: Controlling amcat4 from R},
    author = {Wouter {van Atteveldt} and \textbf{Gruber, Johannes B.}},
    year = {2023},
    url = {https://github.com/ccs-amsterdam/amcat4r},
    note = {R package version 4.0.10.9000},
}

@package{rollama,
  title = {rollama: Communicate with 'Ollama'},
  author = {\textbf{Gruber, Johannes B.} and Weber, Maximilian},
  year = {2024},
  note = {R package version 0.0.2},
  url = {https://CRAN.R-project.org/package=rollama},
  downloads = {Cranlogs download count: 5,978},
}


@package{atrrr,
  title = {atrrr: Wrapper for the AT Protocol Behind 'Bluesky'},
  author = {\textbf{Gruber, Johannes B.} and Benjamin Guinaudeau and Fabio Votta},
  year = {2024},
  note = {R package version 0.0.2, https://github.com/JBGruber/atrrr},
  url = {https://jbgruber.github.io/atrrr/},
  downloads = {Cranlogs download count: 3,688},
}


@package{spacyr,
  title = {spacyr: Wrapper to the 'spaCy' 'NLP' Library},
  author = {Kenneth Benoit and Akitaka Matsuo and \textbf{Gruber, Johannes B.}},
  year = {2023},
  note = {R package version 1.3.0},
  url = {https://CRAN.R-project.org/package=spacyr},
  downloads = {Cranlogs download count: 362,064},
}


@package{quanteda.textmodels,
  title = {quanteda.textmodels: Scaling Models and Classifiers for Textual Data},
  author = {Kenneth Benoit and Kohei Watanabe and Haiyan Wang and Patrick O. Perry and Benjamin Lauderdale and Johannes Gruber and William Lowe},
  year = {2023},
  note = {R package version 0.9.6},
  url = {https://CRAN.R-project.org/package=quanteda.textmodels},
  downloads = {Cranlogs download count: 159,229},
}


@package{askgpt,
  title = {askgpt. A chat package connecting to {API} endpoints by {'OpenAI'} to answer questions (about R).},
  author = {\textbf{Gruber, Johannes B.}},
  year = {2023},
  url = {https://github.com/JBGruber/askgpt},
  note = {R package version 0.1.3},
  downloads = {Cranlogs download count: 9,381},
}


@article{Gamestop.2023,
  title ={The tension between connective action and platformisation: Disconnected action in the {G}ame{S}top short squeeze},
	author = {Michael Vaughan and \textbf{Gruber, Johannes B.} and Ana Inés Langer},
	journal = {New Media \& Society},
	year = {2023},
  doi = {10.1177/14614448231182617},
  url = {https://doi.org/10.1177/14614448231182617},
}

@article{CCR.2024,
  title ={What makes computational communication science (ir)reproducible?},
	author = {Chan*, Chung-hong and Schatto-Eckrodt, Tim and \textbf{Gruber, Johannes B.}},
	journal = {Computational Communication Research},
	year = {2024},
  doi = {10.5117/CCR2024.1.5.CHAN},
  url = {https://doi.org/10.5117/CCR2024.1.5.CHAN},
}

@article{gruber2024rollama,
  title={rollama: An {R} package for using generative large language models through Ollama}, 
  author={\textbf{Gruber, Johannes B.} and Weber, Maximilian},
  year={2024},
  eprint={2404.07654},
  archivePrefix={arXiv},
  doi = {10.48550/arXiv.2404.07654},
  url = {https://doi.org/10.48550/arXiv.2404.07654},
}

@article{software_doc,
  title={A Research Note on Rethinking Software Documentation: Creating Inclusive Computational Tools for Social Sciences}, 
  author={\textbf{Gruber, Johannes B.} and van der Velden, Mariken A. C. G.},
  year={2024},
  archivePrefix={OSF},
  doi = {10.31219/osf.io/a3kwf},
  url = {https://doi.org/10.31219/osf.io/a3kwf},
}

@article{nonconsumptive,
  title = {Sharing is Caring (about Research): Three Avenues for Sharing (Copyrighted) Text Collections and the Need for Non-Consumptive Research},
	author = {\textbf{Gruber, Johannes B.} and van Atteveldt, Wouter and Welbers, Kasper},
	url = "https://opted.eu/fileadmin/user_upload/k_opted/OPTED_Deliverable_D7.6.pdf",
	year = {2023},
}

@InCollection{llm,
  author    = {\textbf{Gruber, Johannes B.} and Votta, Fabio},
  title     = {Large Language Models},
  booktitle = {Elgar Encyclopedia of Political Communication},
  editor    = {Nai, A. and Grömping, M. and Wirz, D.},
  publisher = {Edward Elgar Publishing},
  year      = {2025},
  doi       = {10.31219/osf.io/s7qx2},
  url       = {https://doi.org/10.31219/osf.io/s7qx2},
  note      = {Accepted version},
}


@misc{weaponizing2024,
	title = {Weaponizing rights: {Political} {Uses} of {LGBTQ}+ {Rhetoric} in {Media} {Outlets}},
	copyright = {https://creativecommons.org/licenses/by/4.0/legalcode},
	shorttitle = {Weaponizing rights},
	url = {https://osf.io/dyuwa},
	doi = {10.31219/osf.io/dyuwa},
	abstract = {Our study examines political parties’ rhetorical expressions of selective liberalism in the media, where political parties adopt progressive rhetoric on LGBTQ+ rights while advancing exclusionary stances on immigrants and ethnic minorities. Analyzing 25 years of The Guardian coverage, we explore how LGBTQ+ rights are strategically used to signal inclusivity while reinforcing nativist agendas. The methodological innovation employs generative AI to analyze political rhetoric at scale. Using generative AI, we identified and annotated 1,127 paragraphs referencing LGBTQ+ issues and political parties from 36,000+ articles. Sentiment analysis classified statements as positive, neutral, or negative toward LGBTQ+ rights. Selective liberalism was operationalized as positive framing of LGBTQ+ issues co-occurring with negative framing of immigrants or ethnic minorities. Classifications were validated through qualitative checks to ensure consistency with theoretical expectations. Findings show selective liberalism is widespread, with conservative parties employing it most often, while center-left parties occasionally engage in similar patterns. Temporal analysis reveals a rise in selective liberalism as LGBTQ+ issues gained media prominence, particularly during moments of political polarization. Our research contributes to understanding homonationalism and the instrumentalization of liberal values. Methodologically, it demonstrates the potential of generative AI for large-scale analysis of political rhetoric, combining precision with theoretical insight. By uncovering subtle rhetorical strategies, this study advances computational text analysis and highlights the intersection of progressive advocacy and exclusionary politics.},
	urldate = {2024-12-23},
	publisher = {Open Science Framework},
	author = {\textbf{Gruber, Johannes B.} and Ortega, Alberto Lopez and Van Der Velden, Mariken Anna Catharina Geertruida},
	month = dec,
	year = {2024},
}