Artificial Intelligence, Social Media and Supply Chain Management: The Way Forward
| Autor: | Erik Cambria, Apalak Khatua, Xu Chi, Aparup Khatua |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
supply chain management
Supply chain management TK7800-8360 Computer Networks and Communications Computer science social media Sentiment analysis Complex network computer.software_genre Data science Information extraction AI Hardware and Architecture Control and Systems Engineering context-aware sentiment analysis Signal Processing Social media Electronics Electrical and Electronic Engineering Relevant information computer Overall efficiency |
| Zdroj: | Electronics, Vol 10, Iss 2348, p 2348 (2021) |
| ISSN: | 2079-9292 |
| DOI: | 10.3390/electronics10192348 |
| Popis: | Supply chain management (SCM) is a complex network of multiple entities ranging from business partners to end consumers. These stakeholders frequently use social media platforms, such as Twitter and Facebook, to voice their opinions and concerns. AI-based applications, such as sentiment analysis, allow us to extract relevant information from these deliberations. We argue that the context-specific application of AI, compared to generic approaches, is more efficient in retrieving meaningful insights from social media data for SCM. We present a conceptual overview of prevalent techniques and available resources for information extraction. Subsequently, we have identified specific areas of SCM where context-aware sentiment analysis can enhance the overall efficiency. |
| Databáze: | OpenAIRE |
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