REAL

Bridging Natural Language Processing AI technique and Corporate Communications

Pintér, Dániel Gergő and Ihász, Péter Lajos (2019) Bridging Natural Language Processing AI technique and Corporate Communications. INFORMÁCIÓS TÁRSADALOM: TÁRSADALOMTUDOMÁNYI FOLYÓIRAT, 19 (4). pp. 77-99. ISSN 1587-8694

[img]
Preview
Text
inftars.XIX.2019.4.6.pdf
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview

Abstract

Today’s communication channels and media platforms generate a huge amount of data, which - through advanced AI- (Machine Learning) based techniques - can be leveraged to significantly enhance business networking, improve the efficiency of public relations, management, and extend the possible application areas of communication components. As a sub-discipline of AI, Natural Language Processing (NLP) is frequently utilized in the field of corporate communications (CC) to boost target- group satisfaction through information retrieval and automated dialogue services. This paper gives an overview of the use of NLP in different disciplines of CC, discusses general corporational/organizational practices, and identifies promising research topics for the future while pointing out the ethical aspects of user-data handling and customer engagement. The findings of this synthesizing study are based on primer qualitative research building on the methodology of deep interviews and focus group research involving experts practicing in the fields of CC and NLP. Based on the feedbacks of the participants, a refined CC model was developed, as well as a model mapping conventional NLP techniques onto CC disciplines and tasks they are utilized for.

Item Type: Article
Subjects: Q Science / természettudomány > QA Mathematics / matematika > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
SWORD Depositor: MTMT SWORD
Depositing User: Zsolt Baráth
Date Deposited: 13 Sep 2022 12:25
Last Modified: 17 Oct 2023 14:54
URI: http://real.mtak.hu/id/eprint/148546

Actions (login required)

Edit Item Edit Item