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Towards Better Graph Representation: Two-Branch Collaborative Graph Neural Networks for Multimodal Marketing Intention Detection [article]

Lu Zhang, Jian Zhang, Zhibin Li, Jingsong Xu
2021 arXiv   pre-print
Due to the difficulty of network censors, malicious marketing may be capable of harming society. Therefore, it is meaningful to detect marketing intentions online automatically.  ...  However, gaps between multimodal data make it difficult to fuse images and texts for content marketing detection.  ...  With the explosion of media data online, plenty of contents with marketing intentions appear.  ... 
arXiv:2005.08706v3 fatcat:hwx4bbkw2jcpvoh4rp27axnj34

Guest Editorial: Cognitive Analytics of Social Media for Industrial Manufacturing

Ali Kashif Bashir, Shahid Mumtaz, Varun G. Menon, Kim Fung Tsang
2021 IEEE Transactions on Industrial Informatics  
Social media augments as a nontrivial element to this industrial value chain with the intent of making it more efficient.  ...  The article "Fast and Accurate Convolution Neural Network for Detecting Manufacturing Data" introduces a clustering technique with particle for object detection (CPOD).  ... 
doi:10.1109/tii.2020.3028762 fatcat:t7ghwwqy2nb3llnaghl4b6a4mq

Stacking-Based Ensemble Learning of Self-Media Data for Marketing Intention Detection

Yufeng Wang, Shuangrong Liu, Songqian Li, Jidong Duan, Zhihao Hou, Jia Yu, Kun Ma
2019 Future Internet  
To this end, this paper proposes a machine learning method to identify marketing intentions from large-scale We-Media data.  ...  Therefore, it is necessary to identify news with marketing intentions for life. We follow the idea of text classification to identify marketing intentions.  ...  Acknowledgments: The authors appreciate and acknowledge anonymous reviewers for their reviews and guidance. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/fi11070155 fatcat:zdiy5q2inrhunmakjgh2iytdpu

Multimodal Marketing Intent Analysis for Effective Targeted Advertising

Lu Zhang, Jialie Jerry Shen, Jian Zhang, Jingsong Xu, Zhibin Li, Yazhou Yao, Litao Yu
2021 IEEE transactions on multimedia  
Her research interests include machine learning and deep learning for multimodal media data analysis. She has published several papers in top journals including TMM.  ...  A self-paced learning mechanism is proposed for email intent detection by leveraging user actions as a source of weak supervision [12] .  ...  We focus on marketing intent inferring based on multimodal data. On the other hand, some works [21] , [22] , [23] focus on marketing information detection in media platforms.  ... 
doi:10.1109/tmm.2021.3073267 fatcat:eecdpyhryvgfxmnjuxy3n6ehqi

Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications [article]

Shaoxiong Ji and Shirui Pan and Xue Li and Erik Cambria and Guodong Long and Zi Huang
2020 arXiv   pre-print
engineering or deep learning for automatic detection based on online social contents.  ...  Current suicidal ideation detection methods include clinical methods based on the interaction between social workers or experts and the targeted individuals and machine learning techniques with feature  ...  Based on their social media data, artificial intelligence (AI) and machine learning techniques can predict people's likelihood of suicide [11] , which can better understand people's intention and pave  ... 
arXiv:1910.12611v2 fatcat:63z4uvh5zrgyzb2bawtlbuo34m

The power of prediction with social media

Harald Schoen, Daniel Gayo-Avello, Panagiotis Takis Metaxas, Eni Mustafaraj, Markus Strohmaier, Peter Gloor, Daniel Gayo-Avello, Panagiotis Takis Metax
2013 Internet Research  
For a definitive version of this work, please refer to the published source.  ...  Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document.  ...  Acknowledgements The work of P. Metaxas and E. Mustafaraj was supported by NSF grant CNS-117693.  ... 
doi:10.1108/intr-06-2013-0115 fatcat:eov7zbofhrdztgwpqkdbx42woq

AI-Driven Contextual Advertising: A Technology Report and Implication Analysis [article]

Emil Häglund, Johanna Björklund
2022 arXiv   pre-print
The bids are typically based on information about the user, and to an increasing extent, on information about the surrounding media context.  ...  The transition is further accelerated by developments in Artificial Intelligence (AI), which allow for a deeper semantic understanding of context and, by extension, more effective ad placement.  ...  Moreover, AI systems based on reinforcement learning can be sensitive to noisy data in the early stages of the learning process, where it must base its decisions on relatively few observations.  ... 
arXiv:2205.00911v1 fatcat:qju7bjletjeurah6lrakzrv24m

Social media intention mining for sustainable information systems: categories, taxonomy, datasets and challenges

Ayesha Rashid, Muhammad Shoaib Farooq, Adnan Abid, Tariq Umer, Ali Kashif Bashir, Yousaf Bin Zikria
2021 Complex & Intelligent Systems  
Similarly, six important types of data sets used for this purpose have also been discussed in this work.  ...  The analysis reveals that there exist eight prominent categories of intention. Furthermore, a taxonomy of the approaches and techniques used for intention mining have been discussed in this article.  ...  In [74] online survey method (from 402 participants) was used to detect the reasons to repost a marketing message on social media.  ... 
doi:10.1007/s40747-021-00342-9 fatcat:ak3y4ao2sbffjd5b3rbttidvjy

Data science and AI in FinTech: An overview [article]

Longbing Cao, Qiang Yang, Philip S. Yu
2021 arXiv   pre-print
blockchain, and the DSAI techniques including complex system methods, quantitative methods, intelligent interactions, recognition and responses, data analytics, deep learning, federated learning, privacy-preserving  ...  The research on data science and AI in FinTech involves many latest progress made in smart FinTech for BankingTech, TradeTech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and  ...  modeling and attention mechanisms of predicting data quality issues.  ... 
arXiv:2007.12681v2 fatcat:jntzuwaktjg2hmmjypi5lvyht4

Research on efficient feature extraction: Improving YOLOv5 backbone for facial expression detection in live streaming scenes

Zongwei Li, Jia Song, Kai Qiao, Chenghai Li, Yanhui Zhang, Zhenyu Li
2022 Frontiers in Computational Neuroscience  
This paper proposes an efficient feature extraction network based on the YOLOv5 model for detecting anchors' facial expressions.  ...  Plentiful sensory input delivered by marketing anchors' facial expressions to audiences can stimulate consumers' identification and influence decision-making, especially in live streaming media marketing  ...  This paper selects multiple live videos of four anchors as the data source for a self-built dataset to bridge the gap of facial expression data in live streaming media scenes.  ... 
doi:10.3389/fncom.2022.980063 fatcat:x2tmyz54xnafhkhaqmolhphd4y

Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements [article]

Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu
2020 arXiv   pre-print
We hope this book to be a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly  ...  labeled data.  ...  Acknowledgements This material is based upon work supported by, or in part by, ONR N00014-17-1-2605, N000141812108, NSF grants #1742702, #1820609, #1915801. This work has been inspired by Dr.  ... 
arXiv:2001.00623v1 fatcat:zcmgzbudjvab3fckajrmrbppoy

Sosyal Medya Analitiğinde Makine Öğrenmesi Uygulamaları: Literatür İncelemesi

2020 Journal of Yasar University  
Social media analytics (SMA), referring to the collection and analysis of user generated data from social media platforms, attract attention of both researchers and practitioners striving to derive consumer  ...  As machine learning applications draw attention as a fertile area that may re-shape the future of SMA, there is a need to comprehend trends and approaches in an integrative framework.  ...  SVM technique for measuring purchase intention and lexicon-based approach for sentiment analysis, and concluded that tweet volume and purchase intention discloses a noteworthy gap between the market leader  ... 
doi:10.19168/jyasar.687093 fatcat:mpdypym24fcjrjhocsz7372z2e

AI in Finance: Challenges, Techniques and Opportunities [article]

Longbing Cao
2021 arXiv   pre-print
We then structure and illustrate the data-driven analytics and learning of financial businesses and data.  ...  The comparison, criticism and discussion of classic vs. modern AI techniques for finance are followed.  ...  In addition, the significance of different sources of data in contributing to a learning task can be modeled in terms of various types of attentions, such as multi-head attentions or hierarchical attentions  ... 
arXiv:2107.09051v1 fatcat:g62cz4dqt5dcrbckn4lbveat3u

Comparative Study of Various Approaches, Applications and Classifiers for Sentiment Analysis

Prajval Sudhir, Varun Deshakulkarni Suresh
2021 Global Transitions Proceedings  
Sentiment analysis is contextual mining of text which identifies and extracts subjective information in textual data. sentiment analysis proves to be an incredible asset for users to extract essential  ...  All these sources are constantly generating huge volumes of text data every second. And because of these huge volumes of text data NLP becomes a vital resource in understanding the textual content.  ...  Intent-based Sentiment Analysis Intent classification refers to the automatic classification of textual data which is based on the customer's aim.  ... 
doi:10.1016/j.gltp.2021.08.004 fatcat:sktxcdw33fho7juorhmwa7fkrm

Empathic media and advertising: Industry, policy, legal and citizen perspectives (the case for intimacy)

Andrew McStay
2016 Big Data & Society  
Less obviously, the mechanism for buying out-of-home media space is determined by specialist media buyers that dictate the out-ofhome market.  ...  media forms and modes of emotion detection).  ... 
doi:10.1177/2053951716666868 fatcat:njdclqmq6neldjjai27pcm7evq
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