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bibliographie.bib
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@online{twitter-agb,
author = {Twitter Inc.},
title = {Twitter Allgemeine Geschäftsbedingungen},
date = {2021-06-18},
url = {https://twitter.com/de/tos},
}
@book{python-sm-analysis,
author = {Siddhartha Chatterjee, Michal Krystyanczuk
},
title = {Python Social Media Analysis},
date = {2017-07},
volume = {1},
publisher = {Packt Publishing Ltd.},
location = {Birmingham},
}
@online{negativ-tweet,
author = {Barbara Stifter},
title = {Tweet},
date = {2021-19-06},
url = {https://twitter.com/Babsy1963/status/1364112098964471817},
}
@thesis{dbscan,
author = {Martin Ester, Hans-Peter Kriegel},
title = {A Density-Based Algorithm for Discovering Clusters},
type = {Paper},
institution = {University of Munich},
date = {1996},
}
@misc{neato,
author = {Stephen C. North},
title = {Drawing graphs with NEATO},
date = {2004-04-26},
url = {http://www.graphviz.org/pdf/neatoguide.pdf},
}
@article{tag_klima_klimafest,
author = {Marcel Heberlein},
title = {Deutschland soll "klimafest" werden},
journaltitle = {tagesschau},
date = {21.10.2020},
url = {https://www.tagesschau.de/inland/klimawandel-massnahmen-bundesregierung-101.html},
}
@article{tag_klima_gefahr,
author = {Dietrich Karl Mäurer},
title = {Klimawandel bleibt größte Gefahr
},
journaltitle = {Tagesschau},
date = {19.01.2021},
url = {https://www.tagesschau.de/wirtschaft/weltwirtschaft/weltrisikobericht-weltwirtschaftsforum-klimawandel-klimaschutz-101.html},
}
@article{tag_klima_realiteat,
author = {Karin Bensch},
title = {Wo der Klimawandel längst Realität ist},
journaltitle = {Tagesschau},
date = {13.12.2019},
url = {https://www.tagesschau.de/ausland/ostafrika-klimawandel-101.html},
}
@article{tag_nahost,
author = {Ilanit Spinner},
title = {Die Gewalt nimmt nicht ab},
journaltitle = {Tagesschau},
date = {17.05.2021},
url = {https://www.tagesschau.de/ausland/asien/israel-angriffe-113.html},
}
% This file was created with Citavi 6.8.0.0
@article{Usino.2019,
author = {Usino, Wendi and Satria, Anton and Hamed, Khalid and Bramantoro, Arif and A, Hasniaty and Amaldi, Wahyu},
year = {2019},
title = {Document Similarity Detection using K-Means and Cosine Distance},
keywords = {cluster;cosine distance;document frequency;document similarity;inverse document frequency;K-means;preprocessing;vector space model},
volume = {10},
number = {2},
issn = {2158107X},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100222},
file = {dede0200-e70f-45f0-b5ab-87340b1623c0:C\:\\Users\\paulr\\AppData\\Local\\Swiss Academic Software\\Citavi 6\\ProjectCache\\xml6fr5bak2b8wzmc0u8amb1ze36pc9l6tpqsa999j0zb\\Citavi Attachments\\dede0200-e70f-45f0-b5ab-87340b1623c0.pdf:pdf}
}
% This file was created with Citavi 6.8.0.0
@misc{Godfrey.21.08.2014,
abstract = {Cluster analysis is a field of data analysis that extracts underlying patterns in data. One application of cluster analysis is in text-mining, the analysis of large collections of text to find similarities between documents. We used a collection of about 30,000 tweets extracted from Twitter just before the World Cup started. A common problem with real world text data is the presence of linguistic noise. In our case it would be extraneous tweets that are unrelated to dominant themes. To combat this problem, we created an algorithm that combined the DBSCAN algorithm and a consensus matrix. This way we are left with the tweets that are related to those dominant themes. We then used cluster analysis to find those topics that the tweets describe. We clustered the tweets using k-means, a commonly used clustering algorithm, and Non-Negative Matrix Factorization (NMF) and compared the results. The two algorithms gave similar results, but NMF proved to be faster and provided more easily interpreted results. We explored our results using two visualization tools, Gephi and Wordle.},
author = {Godfrey, Daniel and Johns, Caley and Meyer, Carl and Race, Shaina and Sadek, Carol},
date = {21.08.2014},
title = {A Case Study in Text Mining: Interpreting Twitter Data From World Cup Tweets},
url = {http://arxiv.org/pdf/1408.5427v1},
keywords = {Computer Science - Computation and Language;Computer Science - Information Retrieval;Computer Science - Learning;Statistics - Machine Learning},
file = {51d5dd81-d3de-40bf-bea8-ec37e4f12157:C\:\\Users\\paulr\\AppData\\Local\\Swiss Academic Software\\Citavi 6\\ProjectCache\\xml6fr5bak2b8wzmc0u8amb1ze36pc9l6tpqsa999j0zb\\Citavi Attachments\\51d5dd81-d3de-40bf-bea8-ec37e4f12157.pdf:pdf;312d8c2a-f872-4814-8cb2-a671e3cdb198:C\:\\Users\\paulr\\AppData\\Local\\Swiss Academic Software\\Citavi 6\\ProjectCache\\xml6fr5bak2b8wzmc0u8amb1ze36pc9l6tpqsa999j0zb\\Citavi Attachments\\312d8c2a-f872-4814-8cb2-a671e3cdb198.pdf:pdf;2cc4d3b9-97e8-4eda-856a-0915ad4d173f:C\:\\Users\\paulr\\AppData\\Local\\Swiss Academic Software\\Citavi 6\\ProjectCache\\xml6fr5bak2b8wzmc0u8amb1ze36pc9l6tpqsa999j0zb\\Remote Attachments\\2cc4d3b9-97e8-4eda-856a-0915ad4d173f.pdf:pdf}
}
@online{schunke,
author={Amelie Graen},
date={2021-07-08},
title={Anabel Schunke ist eine der wichtigsten Figuren der neurechten Szene: Wir waren mit ihr feiern},
url={https://www.focus.de/panorama/welt/panorama-anabel-schunke-ist-eine-der-wichtigsten-figuren-der-neurechten-szene-wir -waren-mit-ihr-feiern_id_10281656.html}}
@online{laszlo,
author={laszlohealth},
date={2021-07-08},
year={2021},
title={Tweet},
url={https://twitter.com/laszlohealth/status/1319338449149874181}}
@online{Thomas,
author={Medinside},
title={Verhafteter Aargauer Arzt in der Psychiatrie},
date={2021-07-08},
year={2021},
url={https://www.medinside.ch/de/post/verhafteter-aargauer-arzt-in-der-psychiatrie}}
@inproceedings{Conover2011,
author = {Conover, Michael and Gonçalves, Bruno and Ratkiewicz, Jacob and Flammini, Alessandro and Menczer, Filippo},
year = {2011},
month = {10},
title = {Predicting the Political Alignment of Twitter Users},
}
@online{twitter-mdau,
author = {Twitter Inc.},
year = {2021},
title = {Q1 2021 Letter to Shareholders},
}
@book{Achrekar2011,
author={Achrekar, Harshavardhan and Gandhe, Avinash and Lazarus, Ross and Ssu-Hsin Yu and Liu, Benyuan},
booktitle={2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},
title={Predicting Flu Trends using Twitter data},
year={2011},
}
@online{top-hashtags-de,
author ={Henning Eberhardt},
title = {Twitter 2020: ein Jahresrückblick aus Trends und Hashtags},
year = {2020},
url ={https://www.absatzwirtschaft.de/twitter-2020-ein-jahresrueckblick-mit-trends-und-hashtags-176871/},
}
@online{twitter-tos,
author ={Twitter Inc.},
title = {Twitter Terms of Service},
year = {2021},
url ={https://twitter.com/en/tos},
}
@miscs{Friedemann2015C,
title={Clustering a Customer Base Using Twitter Data},
author={Vanessa Friedemann},
year={2015}
}
@miscs{Miyamoto2021,
author = {Miyamoto, Sadaaki and Suzuki, Shohei and Takumi, Satoshi},
year = {2012},
month = {06},
title = {Clustering in tweets using a fuzzy neighborhood model},
isbn = {978-1-4673-1507-4},
journal = {IEEE International Conference on Fuzzy Systems},
doi = {10.1109/FUZZ-IEEE.2012.6250800}
}
@article{Ifrim2014,
author = {Ifrim, Georgiana and Shi, Bichen and Brigadir, Igor},
year = {2014},
month = {01},
title = {Event detection in Twitter using aggressive filtering and hierarchical tweet clustering},
volume = {1150},
journal = {CEUR Workshop Proceedings}
}
@miscs{Conover2011-2,
author = {Conover et al.},
year = {2011},
month = {10},
title = {Predicting the Political Alignment of Twitter Users},
}
@book{Sechelea2016,
author = {Mr. Andrei Sechelea et al.},
year = {2016},
title = {Twitter Data Clustering and Visualization},
url = {http://ieeexplore.ieee.org/servlet/opac?punumber=7495173},
keywords = {big data;clustering;social media;Twitter;visualization},
address = {Piscataway, NJ},
publisher = {IEEE},
isbn = {9781509019908},
institution = {International Conference on Telecommunications and ICT}
}
% This file was created with Citavi 6.8.0.0
@misc{Godfrey2014,
author = {Godfrey etal.},
date = {21.08.2014},
title = {A Case Study in Text Mining: Interpreting Twitter Data From World Cup Tweets},
year = {2014},
url = {http://arxiv.org/pdf/1408.5427v1},
keywords = {Computer Science - Computation and Language;Computer Science - Information Retrieval;Computer Science - Learning;Statistics - Machine Learning},
}
@article{Kharde2016,
author = {Kharde, Vishal and Sonawane, Sheetal},
year = {2016},
month = {04},
pages = {5-15},
title = {Sentiment Analysis of Twitter Data: A Survey of Techniques},
volume = {139},
journal = {International Journal of Computer Applications},
doi = {10.5120/ijca2016908625}
}
@online{hassrede,
author = {Johannes Baldauf, Julia Ebner und Jakob Guhl},
title = {Hassrede und
Radikalisierung
im Netz},
date = {2021-07-14},
url = {http://www.isdglobal.org/wp-content/uploads/2018/09/ISD-NetzDG-Report-German-FINAL-26.9.18.pdf},
}
@article{fake-news,
author={Alexandre Bovet and Hernán A. Makse},
title={Influence of fake news in Twitter during the 2016 US presidential election},
year={2019},
journal={Nature Communications}}
@online{lemma,
author = {Nicky Reinert},
title = {Einführung in Stemming und Lemmatisierung deutscher Texte mit Python},
date = {09.12.2020},
url = {https://nickyreinert.de/blog/2020/12/09/einfuehrung-in-stemming-und-lemmatisierung-deutscher-texte-mit-python/},
month = {12},
year = {2020},
urldate = {17.07.2021},
}
% This file was created with Citavi 6.8.0.0
@incollection{Borg.2010,
author = {Borg, Ingwer},
title = {Multidimensionale Skalierung},
pages = {391--418},
publisher = {{VS Verlag f{\"u}r Sozialwissenschaften}},
isbn = {978-3-531-16339-0},
editor = {Wolf, Christof and Best, Henning},
booktitle = {Handbuch der sozialwissenschaftlichen Datenanalyse},
year = {2010},
address = {Wiesbaden},
doi = {10.1007/978-3-531-92038-2{\textunderscore }17},
file = {c9e9c8c6-f14e-4756-bc77-fc488264edd7:C\:\\Users\\paulr\\AppData\\Local\\Swiss Academic Software\\Citavi 6\\ProjectCache\\xml6fr5bak2b8wzmc0u8amb1ze36pc9l6tpqsa999j0zb\\Citavi Attachments\\c9e9c8c6-f14e-4756-bc77-fc488264edd7.pdf:pdf}
}
@online{tone_ibm,
author = {IBM},
title = {IBM Tone Analyser },
date = {18.07.2021},
url = {https://www.ibm.com/de-de/cloud/watson-tone-analyzer},
}