Thomas Mandl

Prof. Dr. Thomas Mandl

Information Science and Language Technology, University of Hildesheim, Hildesheim, Lower Saxony, Germany
orcid
Professor for Information Science

Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2020 in Expert Systems with Applications
Verified
Journal Article
Closed access
SMSandip Modha
Sandip Modha
PMPrasenjit Majumder
Prasenjit Majumder
Thomas MandlThomas Mandl
Thomas Mandl
CMChintak Mandalia
Chintak Mandalia

1 January 2009
Verified
Book Chapter
Closed access
PDF file
EAEneko Agirre
Eneko Agirre
Giorgio Maria Di NunzioGiorgio Maria Di Nunzio
Giorgio Maria Di Nunzio
NFNicola Ferro
Nicola Ferro
Thomas MandlThomas Mandl
Thomas Mandl
CPCarol Peters
Carol Peters

1 January 2006
Verified
Conference Paper
Closed access
AKA. Kralisch
A. Kralisch
Thomas MandlThomas Mandl
Thomas Mandl
This paper investigates the role of language in accessing information on the Internet. We combined data about website visitors through log-file analysis with data about web-hosts and links obtained from a crawler. Results suggest that language may represent a double barrier: first, the number of native speakers determines the number of web-hosts, and hence the amount of information and the interconnectedness of information sources. Second, to access information on a particular website the languages offered are an even more important factor than network effects: non-native speakers and links from websites in other languages are always underrepresented. Our results are in line with the Information Foraging Theory, the Revised Hierarchy Model, network and market theories, and emphasize the role of language on the Internet. Insight into these processes is helpful when website translation represents important investment decisions, or when aiming to diminish the digital divide.

5 April 2022
Verified
Book Chapter
Closed access
PDF file
PNPreslav Nakov
Preslav Nakov
ABAlberto Barrón-Cedeño
Alberto Barrón-Cedeño
GMGiovanni Da San Martino
Giovanni Da San Martino
FAFiroj Alam
Firoj Alam
JSJulia Maria Struß
Julia Maria Struß
JBJavier Beltrán
Javier Beltrán

25 August 2022
Verified
Book Chapter
Closed access
PDF file
PNPreslav Nakov
Preslav Nakov
ABAlberto Barrón-Cedeño
Alberto Barrón-Cedeño
GMGiovanni da San Martino
Giovanni da San Martino
FAFiroj Alam
Firoj Alam
JSJulia Maria Struß
Julia Maria Struß
JKJuliane Köhler
Juliane Köhler

9 December 2022
Verified
Conference Paper
Open access
SSShrey Satapara
Shrey Satapara
PMPrasenjit Majumder
Prasenjit Majumder
Thomas MandlThomas Mandl
Thomas Mandl
SMSandip Modha
Sandip Modha
HMHiren Madhu
Hiren Madhu
DPDamith Premasiri
Damith Premasiri
In recent years, the spread of online offensive content has become of great concern, motivating researchers to develop robust systems capable of identifying such content automatically. To carry out a fair evaluation of these systems, several international shared tasks have been organized, providing the community with essential benchmark data and evaluation methods for various languages. Organized since 2019, the HASOC (Hate Speech and Offensive Content Identification) shared task is one of these initiatives. In its fourth iteration, HASOC 2022 included three tasks for English-Hindi codemix, German and Marathi. Tasks 1 and 2 were on conversational hate speech detection. The idea is to detect supporting hate speech, profanity, or other forms of offensiveness depending on the surrounding context of Twitter posts. Task 1 was offered in Hindi-English codemix and German. Task 2 was provided for Hindi-English codemix, and it was focused on further classifying the problematic tweets in conversational hate speech into standalone and contextual hate. This paper presents a brief description of tasks, data, and participation.