Autor: Lorek, K. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Automated credibility assessment on twitter
Autorzy:: Lorek, K.
Suehiro-Wiciński, J.
Jankowski-Lorek, M.
Gupta, A.
Powiązania:: https://bibliotekanauki.pl/articles/952935.pdf
Data publikacji:: 2015
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: Twitter
credibility
machine learning algorithms
Opis:: In this paper, we make a practical approach to automated credibility assessment on Twitter. We describe the process behind the design of an automated classifier for information credibility assessment. As an addition, we propose practical implementation of TwitterBOT, a tool which is able to score submitted tweets while working in the native Twitter interface.
Źródło:: Computer Science; 2015, 16 (2); 157-168
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Document controversy classification based on the wikipedia category structure
Autorzy:: Jankowski-Lorek, M.
Zieliński, K.
Powiązania:: https://bibliotekanauki.pl/articles/305229.pdf
Data publikacji:: 2015
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: Wikipedia
controversy
classification
Opis:: Dispute and controversy are parts of our culture and cannot be omitted on the Internet (where it becomes more anonymous). There have been many studies on controversy, especially on social networks such as Wikipedia. This free on-line encyclopedia has become a very popular data source among many researchers studying behavior or natural language processing. This paper presents using the category structure of Wikipedia to determine the controversy of a single article. This is the first part of the proposed system for classification of topic controversy score for any given text.
Źródło:: Computer Science; 2015, 16 (2); 185-198
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

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