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A peer-reviewed article of this preprint also exists.
This version is not peer-reviewed
Submitted:
03 January 2024
Posted:
04 January 2024
You are already at the latest version
Cluster | Cluster Name | Description |
---|---|---|
1 (Red) | Holistic Examination of the Interdisciplinary Landscape in AI Research | This cluster provides a panoramic view of the interdisciplinary landscape in artificial intelligence research, showcasing the breadth and depth of topics covered. Encompassing areas such as ethics, blockchain, advertising, human life, and the potential of generative AI, it underscores the multifaceted nature of AI’s impact on various domains. |
2 (Green) | Multifaceted Analysis of the Societal Impact of Social Media Data | This cluster encapsulates a comprehensive exploration of the societal impact of social media data in the context of various significant factors. |
3 (Blue) | Advanced Techniques in Natural Language Processing (NLP) and Machine Learning | This cluster focuses on the cutting-edgetechniques and methodologies employed in natural language processing (NLP) and machine learning for analyzing textual content, particularly in the context of social media. |
4 (Yellow) | AI-Powered Analysis of Online Content and Social Dynamics | This cluster centers on the application of artificial intelligence in analyzing and understanding the dynamics of online content and social interactions. |
5 (Purple) | Technological Advancements and Ethical Considerations | This cluster delves into the intersection of technological advancements and ethical considerations within the field of artificial intelligence. |
6 (Sky Blue) | Predictive Modeling and Algorithm Evaluation | This cluster revolves around predictive modeling and algorithmic evaluation in the realm of artificial intelligence. |
7 (Orange) | Knowledge Representation and Analysis Methods | This cluster revolves around the exploration of knowledge graphs and academic perspectives within the context of artificial intelligence. |
8 (Brown) | Neural Network Architecture and Learning | This cluster encompasses discussions related to neural network architecture, learning processes, and associated challenges. |
Cluster | Cluster Name | Description |
---|---|---|
1 (Red) | AI-Enhanced Advertising Ecosystem | The cluster, with its diverse set of terms, provides insights into the multifaceted intersection of AI and advertising, serving as a valuable resource for researchers and practitioners seeking a holistic understanding of the AI-driven advertising ecosystem. |
2 (Green) | Enhanced Sentiment and Misinformation Classification in social media | This cluster aims to contribute significantly to the discourse surrounding sentiment dynamics and misinformation detection in social media contexts relevant to advertising and AI applications. |
3 (Blue) | Comprehensive Exploration of Mental Health and Societal Dynamics | This cluster provides a rich exploration of mental health dynamics within the context of societal influences and online discourse, contributing valuable insights for AI applications in advertising addressing mental health-related issues. |
4 (Yellow) | Surveillance and Methodological Insights in Health Communication | This cluster offers a comprehensive examination of the evolving landscape of health communication, providing methodological insights and technological approaches relevant to AI applications in advertising within the health domain. |
5 (Purple) | Deception Detection and Computational Modeling in NLP | This cluster provides a nuanced view of the intricate techniques and methodologies employed in NLP for deception detection and computational modeling. |
6 (Sky Blue) | Music Consumption and Neuroscientific Insights | This cluster signifies a comprehensive examination of the intricate relationships between music, consumer identity, and neuroscientific aspects, offering valuable insights for advertisers in the music industry. |
7 (Orange) | Knowledge and Social Impact in Tourism | This cluster reflects a multidimensional examination of AI’s contributions to knowledge, societal influences, and their implications for the tourism industry in the realm of advertising. |
8 (Brown) | AI’s Response to the Global Pandemic | The cluster implies a nuanced examination of how AI technologies can assist in managing and mitigating the consequences of a pandemic on a global scale, reflecting the interdisciplinary nature of AI applications in advertising during extraordinary circumstances. |
9 (Pink) | Financial Impact and Social Awareness | This cohesive grouping implies an exploration of how AI can be a valuable tool for financial predictions and simultaneously contribute to socially impactful advertising initiatives, reflecting the diverse applications of AI technologies in advertising. |
10 (Coral) | Appearance | This cluster likely encapsulates discussions related to the visual elements, aesthetics, and overall presentation of content in advertising campaigns. |
Publication Years | |
---|---|
Terms | Years |
tcim | 2022 |
neurosurgery awareness month | 2022 |
palliative care | 2021 |
indirect appeal | 2021 |
self competence | 2021 |
cpss | 2021 |
mgc | 2021 |
ipv | 2021 |
common theme | 2021 |
bpa | 2021 |
Cluster | Cluster Name | Description |
---|---|---|
1 (Red) | AI Impact and Ethical Considerations in Advertising | This cluster provides a comprehensive overview of the broad spectrum of issues related to the impact, ethics, and varied applications of AI in advertising, offering insights into the evolving landscape and the ethical considerations associated with the integration of advanced technologies in the field. |
2 (Green) | Deep Learning in Advertising and Information Retrieval | This cluster provides a comprehensive view of the intersection between deep learning, advertising, and information retrieval, showcasing the diverse applications and challenges within this domain. |
3 (Blue) | Social Media Impact on Mental Health and Public Health Surveillance | The broad scope of this cluster contributes to a nuanced understanding of the complex interplay between social media, mental health, and public health dynamics. |
4 (Yellow) | Machine Learning Applications in Cybersecurity and Advertisement | This cluster provides insights into the multifaceted applications of machine learning techniques in enhancing cybersecurity measures and optimizing advertising strategies. |
5 (Purple) | Deception Detection and Computational Modeling in NLP | This cluster provides a nuanced view of the intricate techniques and methodologies employed in NLP for deception detection and computational modeling. |
6 (Sky Blue) | Crisis Management and Data-Driven Decision-Making | This cluster provides insights into the multifaceted aspects of crisis management, emphasizing the role of data-driven decision-making and advanced technologies in addressing challenges. |
7 (Orange) | Emerging Technologies and Big Data Integration | This cluster provides insights into the evolving landscape of emerging technologies, big data utilization, and their multifaceted integration across various domains. |
8 (Brown) | Predictive Analytics and Personalization Strategies | This cluster provides insights into the evolving landscape of predictive analytics, its diverse applications, and the integration of human-AI collaboration for personalized experiences. |
9 (Pink) | Social Media Analysis and Communication Dynamics | This cluster is centered around the analysis of social media, particularly Twitter, and the dynamics of online communication. Additionally, the cluster delves into computational methods, linguistic analysis, and visual analytics to unravel patterns in online content. |
10 (Coral) | Business Intelligence and Consumer Insights | This cluster revolves around business intelligence, consumer insights, and the analysis of user-generated content. |
11 (Mint) | Text Analysis in Sentiment Classification | The cluster includes techniques like gradient boosting, naive Bayes classification, and embeddings, emphasizing the employment of various machine learning approaches for effective text analysis in the domain of disaster management and sentiment classification. |
12 (Pastel Blue) | Advanced Natural Language Processing and Text Analysis | This cluster focuses on various aspects of natural language processing (NLP) and machine learning techniques applied to text and language analysis. |
Centrality | Link Strength | Documents | |||||||
---|---|---|---|---|---|---|---|---|---|
Keywords | Degree | Keywords | Betweenness | Keywords | Closeness | Keywords | Tie Strength | Keywords | Occurrences |
machine learning | 806 | machine learning | 60748.198 | machine learning | 0.891 | machine learning | 6805 | machine learning | 1644 |
social media | 740 | social media | 43256.645 | social media | 0.837 | social media | 5714 | social media | 1213 |
595 | 21682.789 | 0.739 | 3445 | sentiment analysis | 718 | ||||
deep learning | 527 | deep learning | 19698.834 | deep learning | 0.701 | sentiment analysis | 3144 | 686 | |
sentiment analysis | 515 | classification | 16078.697 | sentiment analysis | 0.695 | deep learning | 2509 | deep learning | 593 |
classification | 505 | sentiment analysis | 15862.208 | classification | 0.689 | classification | 2094 | classification | 444 |
big data | 462 | artificial intelligence | 13931.537 | big data | 0.668 | natural language processing | 1899 | natural language processing | 425 |
artificial intelligence | 459 | big data | 11645.331 | artificial intelligence | 0.666 | big data | 1543 | artificial intelligence | 397 |
natural language processing | 425 | model | 10273.965 | natural language processing | 0.65 | artificial intelligence | 1412 | big data | 298 |
model | 406 | natural language processing | 10023.799 | model | 0.641 | covid-19 | 1140 | covid-19 | 224 |
Keyword | Publication Year |
---|---|
generative ai | 2022 |
social media platforms | 2022 |
digital media | 2022 |
accessibility | 2022 |
perspective | 2022 |
social media use | 2022 |
inclusion | 2022 |
ai ethics | 2022 |
data classification | 2022 |
theme | 2022 |
Centrality | Link Strength | Documents | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Countries | Degree | Countries | Betweenness | Countries | Closeness | Countries | Tie Strength | Countries | Publications | ||
usa | 58 | usa | 383.8 | usa | 0.835 | usa | 511 | usa | 1808 | ||
england | 57 | england | 332.621 | england | 0.835 | china | 294 | china | 925 | ||
india | 53 | india | 277.31 | india | 0.789 | england | 260 | india | 834 | ||
france | 43 | france | 162.213 | france | 0.717 | india | 157 | england | 479 | ||
china | 42 | china | 108.698 | china | 0.71 | germany | 125 | germany | 272 | ||
germany | 40 | germany | 77.019 | germany | 0.689 | france | 83 | south korea | 186 | ||
netherlands | 33 | netherlands | 72.584 | netherlands | 0.651 | netherlands | 77 | france | 148 | ||
egypt | 29 | croatia | 71.427 | egypt | 0.623 | south korea | 68 | netherlands | 114 | ||
ireland | 27 | egypt | 58.887 | belgium | 0.612 | singapore | 60 | taiwan | 112 | ||
sweden | 26 | belgium | 50.789 | ireland | 0.612 | switzerland | 49 | turkey | 103 |
Co-occurrences of Terms Analysis | |||||||||
---|---|---|---|---|---|---|---|---|---|
Centrality | Link Strength | Occurrences | |||||||
Terms | Degree | Terms | Betweenness | Terms | Closeness | Terms | Tie Strength | Terms | Occurrences |
learning | 900 | learning | 3891.907 | accuracy | 0.997 | learning | 30037 | learning | 2554 |
accuracy | 887 | dataset | 3692.864 | dataset | 0.983 | accuracy | 19563 | accuracy | 1550 |
dataset | 886 | accuracy | 3678.043 | text | 0.982 | dataset | 18453 | dataset | 1515 |
text | 868 | text | 3407.614 | 0.963 | sentiment | 14420 | detection | 1149 | |
861 | detection | 3338.448 | tweet | 0.956 | detection | 13900 | sentiment | 1104 | |
tweet | 856 | 3294.642 | sentiment | 0.951 | text | 13842 | text | 1092 | |
sentiment | 856 | tweet | 3238.677 | technology | 0.951 | 13241 | 1017 | ||
technology | 854 | technology | 3230.757 | detection | 0.949 | tweet | 13070 | tweet | 1002 |
detection | 853 | development | 3226.166 | development | 0.948 | classifier | 10790 | technology | 856 |
development | 845 | sentiment | 3213.324 | classifier | 0.94 | technology | 10587 | classifier | 832 |
Terms | Years |
---|---|
chatgpt | 2022 |
longitudinal | 2022 |
bidirectional | 2021 |
generative ai | 2021 |
preferred reporting item | 2021 |
bert | 2021 |
explainability | 2021 |
knowledge graph | 2021 |
count vectorizer | 2021 |
technological advancement | 2021 |
Centrality | Link Strength | Occurrences | |||||||
---|---|---|---|---|---|---|---|---|---|
Terms | Degree | Terms | Betweenness | Terms | Closeness | Terms | Tie Strength | Terms | Occurrences |
technology | 1162 | technology | 16790.033 | technology | 0.867 | tweet | 46375 | tweet | 2576 |
tweet | 1156 | tweet | 15333.087 | tweet | 0.864 | coronavirus | 30215 | sentiment | 1651 |
knowledge | 1104 | role | 14404.801 | knowledge | 0.837 | sentiment | 28546 | sentiment analysis | 1555 |
post | 1095 | knowledge | 14330.311 | post | 0.832 | sentiment analysis | 24835 | technology | 1470 |
language | 1094 | post | 13968.271 | language | 0.832 | technology | 23854 | coronavirus | 1334 |
role | 1090 | advertising | 12845.353 | role | 0.83 | post | 21931 | advertising | 1327 |
media | 1090 | language | 12668.547 | media | 0.83 | language | 18436 | post | 1286 |
sentiment | 1075 | media | 12404.62 | sentiment | 0.822 | word | 17670 | language | 1227 |
sentiment analysis | 1050 | advertisement | 12146.639 | word | 0.81 | artificial intelligence | 16440 | advertisement | 1212 |
word | 1050 | sentiment | 11854.481 | sentiment analysis | 0.81 | advertising | 16191 | artificialintelligence | 1123 |
Centrality | Link Strength | Publications | |||||||
---|---|---|---|---|---|---|---|---|---|
Countries | Degree | Countries | Betweenness | Countries | Closeness | Countries | Tie Strength | Countries | Publications |
usa | 49 | usa | 339.723 | england | 0.836 | usa | 536 | usa | 1808 |
england | 49 | england | 299.647 | usa | 0.824 | england | 346 | england | 479 |
india | 45 | india | 227.772 | india | 0.782 | china | 298 | china | 925 |
china | 35 | china | 99.025 | china | 0.701 | india | 194 | india | 834 |
germany | 33 | germany | 76.234 | germany | 0.678 | germany | 182 | germany | 272 |
malaysia | 27 | malaysia | 68.891 | malaysia | 0.635 | malaysia | 71 | malaysia | 127 |
egypt | 26 | croatia | 61.575 | egypt | 0.629 | switzerland | 69 | switzerland | 69 |
belgium | 22 | egypt | 53.821 | belgium | 0.598 | scotland | 63 | scotland | 68 |
ireland | 21 | belgium | 47.508 | ireland | 0.598 | sweden | 63 | sweden | 87 |
sweden | 20 | qatar | 34.664 | qatar | 0.592 | austria | 58 | austria | 56 |
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