Sentiment and SWOT Analyses of DeepSeek AI
Insights from Media, Self-Perceptions, User Perceptions, and Literature
Bibliographic Data
| ID | 22006295 |
|---|---|
| Authors | Wali Khan Monib (0000-0002-9575-9305, Khost University, corresponding author) |
| Year | 2025 |
| Volume | 15 |
| Issue | 4 |
| Publication date | 2025-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | SAGE Open (JOURNAL) |
| Journal identifiers | ISSN: 2158-2440 • E-ISSN: 2158-2440 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/21582440251395226 |
| OpenAlex | W4416386881 |
| Language | EN |
| References cited | 29 |
This study aims to conduct sentiment analysis and SWOT analysis of DeepSeek. The dataset consisted of four data sources: news articles, DeepSeek self-perception, users’ perceptions, and a comprehensive literature review. Sentiment analysis examined news articles from diverse Chinese and Western outlets, while SWOT analysis evaluated DeepSeek strengths, weaknesses, opportunities, and threats based on DeepSeek self and users’ perceptions and literature. ATLAS.ti and SPSS were used for analysis. Chi-square analysis results revealed significant differences between Chinese and Western media portrayals. Chinese media expressed more positive and fewer negative sentiments, whereas Western media expressed more negative and fewer positive sentiments, with both primarily neutral. Chinese media positive sentiment emphasized innovation, self-reliance, and global AI leadership, while negative sentiment sharply focused on technical and ethical challenges. Western media positive sentiment highlighted efficiency and technological advancement, while negative sentiment emphasized market disruption, geopolitical tensions, and security concerns. The SWOT analysis of DeepSeek self-perception indicated deliberate management of identity and accountability, with user-centered prompts eliciting detailed responses than tool-focused prompts. Users’ perceptions highlighted DeepSeek strengths in efficiency and accessibility, while noting weaknesses in accuracy and ecosystem maturity. Opportunities were identified in education, equity, and interdisciplinary applications, alongside threats related to misinformation, automation risks, and the potential for ethical misuse. The literature corroborated these findings, highlightingstrengths include performance, efficiency, reasoning capabilities, low cost, and open-source deployment;limitations involve data quality, bias, and privacy concerns; opportunities exist in education, industry, and task-specific applications; and threats include reliability and over-reliance
Context analysis · Correspondence analysis · Perception · Sentiment analysis · Social media · Strengths and weaknesses · SWOT Analysis · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI
| Highly cited | No |
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