What is math about? Basically spoken, it is about uniting separate parts and bringing together something new. To understand and to read the new creation, it is important to understand the meaning of each part to create further meaning of the whole. Where is the difference to language? To properly understand a language it is important to split it into smaller units and to understand the meaning of each unit it is necessary and helpful to understand the whole language. The mathematical formula is 1+1= language.
Firstly, this seems to be confusing but lately, logical. Language does consist of smaller units which, once brought together, build up to a new system, a whole language. To understand a language it is therefore indispensable to understand logical connections but it is not necessary to be a math genius. Today’s most striking field of linguistic, Natural Language Processing (NLP), combines the ability to think logically and to analyse language in an encompassing manner.
The aim of this paper is to give a brief introduction on what is Natural Language Processing (NLP) and further, to define several challenges NLP has to face due to online data bias. The challenges which concern the field of technology as well as they influence the social impact form a work frame for the overlaying field of ethical challenges in online data which are going to be displayed in this paper. Not only existing challenges but also future solutions will be a subject of discussion.
CONTENT
Introduction
Part One - What is NLP -
NLP tasks before 1960
NLP tasks after 1960
Part Two - The societal impact factors of NLP -
Avoiding exclusion
Avoiding overgeneralisation
Avoiding overexposure
Underexposure and its negative impact on balanced data
Part Three - Major challenges for online research ethics -
Conclusion
Bibliography
- Quote paper
- Szahel Kumke (Author), 2019, Societal Impact Factors and Major Challenges for Natural Language Processing, Munich, GRIN Verlag, https://www.grin.com/document/1112090
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