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Author Profiling on Social Media: An Ensemble Learning Approach using Various Features

Youngjun Joo, Inchon Hwang
2019 Conference and Labs of the Evaluation Forum  
Acting as a complement to these methods, we investigate an ensemble learning method paves the way to improve the performance of AP tasks.  ...  We describe our participation in the PAN 2019 shared task on author profiling, determine whether a tweet's author is a bot or a human, and in case of human, identify author's gender for English and Spanish  ...  Acting as a complement to these features, we also investigate an ensemble learning method combining classification methods based on various features and BERT model paves the way to improve the performance  ... 
dblp:conf/clef/JooH19 fatcat:7ceztesujncmrpml5b55cxl2jq

Cross-Genre Age and Gender Identification in Social Media

Anam Zahid, Aadarsh Sampath, Anindya Dey, Golnoosh Farnadi
2016 Conference and Labs of the Evaluation Forum  
We then ensemble single-genre predictive models trained on the blog, social media and Twitter data sources, to build our multi-genre ensemble approach.  ...  We use the softvoting approach to build the classification ensemble.  ...  Using the S-G ensemble approach, we incorporate various features extracted from the documents and by using the M-G ensemble approach, not only do we use different features, but also leverage predictive  ... 
dblp:conf/clef/ZahidSDF16 fatcat:npeywd3ew5dddjb5fhfph3shuy

Social Media Writing Style Fingerprint [article]

Himank Yadav, Juliang Li
2017 arXiv   pre-print
We present our approach for computer-aided social media text authorship attribution based on recent advances in short text authorship verification.  ...  The output layer of our system uses an unweighted majority vote vector to arrive at a conclusion.  ...  wrote on different subjects on various forms of social media.  ... 
arXiv:1712.04762v3 fatcat:si2yeivnhvgmzecp2bzbwkqtvy

Media forensics on social media platforms: a survey

Cecilia Pasquini, Irene Amerini, Giulia Boato
2021 EURASIP Journal on Information Security  
The dependability of visual information on the web and the authenticity of digital media appearing virally in social media platforms has been raising unprecedented concerns.  ...  uploaded on social networks, platform provenance analysis allowing to identify sharing platforms, and multimedia verification algorithms assessing the credibility of media objects in relation to its associated  ...  learning approaches.  ... 
doi:10.1186/s13635-021-00117-2 doaj:06be9b5b0da9456b97060870239d1f24 fatcat:fquen2fiyfbazo5b5ydvz3ddae

Offensive Language Recognition in Social Media

Elena Shushkevich, John Cardiff, Paolo Rosso, Liliya Akhtyamova
2020 Journal of Computacion y Sistemas  
This indicates the potential value of the proposed approach in the field of hate speech recognition in social media.  ...  The model created is an ensemble of classical machine learning models included Logistic Regression, Support Vector Machines, Naive Bayes models and a combination of Logistic Regression and Naive Bayes.  ...  Acknowledgements The work of Paolo Rosso was partially funded by the Spanish MICINN under the research project MISMISFAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE  ... 
doi:10.13053/cys-24-2-3376 fatcat:n6opxaivz5ajbcbfin3twvyuji

Computational Sarcasm Analysis on Social Media: A Systematic Review [article]

Faria Binte Kader, Nafisa Hossain Nujat, Tasmia Binte Sogir, Mohsinul Kabir, Hasan Mahmud, Kamrul Hasan
2022 arXiv   pre-print
Our study provides well-summarized tables of sarcasm datasets, sarcastic features and their extraction methods, and performance analysis of various approaches which can help researchers in related domains  ...  Sarcasm can be defined as saying or writing the opposite of what one truly wants to express, usually to insult, irritate, or amuse someone.  ...  After which the learned parameters can be transferred and further tuned on social media based datasets. We found Jamil et al. [68] to have used such multi-domain approach in their study.  ... 
arXiv:2209.06170v2 fatcat:2yspcvkbwfhozddw43w4r763ci

Author Profiling in Social Media with Multimodal Information

Miguel Á. Álvarez Carmona, Esaú Villatoro Tello, Manuel Montes y Gómez, Luis Villaseñor Pineda
2020 Journal of Computacion y Sistemas  
In this thesis work, we propose a solution for the task of profiling authors in social networks.  ...  Our solution uses a multimodal approach to extracting information from Agradecimientos Mamá, no hay palabras para poder agradecerle todo tu apoyo a lo largo de toda una vida y más.  ...  Late fusion strategies consider each feature space independently and build an ensemble learning system to combine the outputs of classifiers trained on different inputs for instance a weighting vote ensemble  ... 
doi:10.13053/cys-24-3-3488 fatcat:dj6rhmdbf5grhngea6hwocxo7q

Computational personality recognition in social media

Golnoosh Farnadi, Geetha Sitaraman, Shanu Sushmita, Fabio Celli, Michal Kosinski, David Stillwell, Sergio Davalos, Marie-Francine Moens, Martine De Cock
2016 User modeling and user-adapted interaction  
Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data.  ...  (2) Which predictive features work well across different online environments? and (3) What is the decay in accuracy when porting models trained in one social media environment to another?  ...  Thus, improving the performance of the dictionary-based approaches on user generated texts in social media is an open path to explore.  ... 
doi:10.1007/s11257-016-9171-0 fatcat:33aojvt255hnljkvsiaoonikiq

A Review on Fake Account Detection in Social Media

Khushboo Saraswat
2020 International Journal for Research in Applied Science and Engineering Technology  
Social media sites are used on a regular basis in today's world, and have become an integral part of our lives.  ...  This paper presents a review of various existing methods for detecting fake accounts in social media.  ...  Yasyn Elyusufi et al.[2020] This paper proposed an approach to the detection of a false profile on the social media site using minimal profile data.  ... 
doi:10.22214/ijraset.2020.32627 fatcat:aabuz7kosvaurdp7vwjtwg7piu

Augmented Machine Learning Ensemble Extension Model for Social Media Health Trends Predictions

2019 International journal of recent technology and engineering  
Ensemble Learning wherein an array of various Machine Learning techniques can be employed to achieve better classification or clustering results.  ...  Social networks have been studied and analyzed using various graph-based analysis techniques. Prominent analysishas centered on features like ego-networks, distance, centrality, sub-networks etc.  ...  Social networks have been studied and analyzed using various graph-based analysis techniques. Prominent analysishas centered on features like ego-networks, distance, centrality, sub-networks etc.  ... 
doi:10.35940/ijrte.b1091.0782s719 fatcat:f57k7bqqojg4vimz7vqrvjmxnu

An Ensemble Framework for Spam Detection on Social Media Platforms

Junzhang Wang, Courant Institute of Mathematical Sciences, New York University, New York, NY 10003 USA, Diwen Xue, Karen Shi
2021 International Journal of Machine Learning and Computing  
Furthermore, our framework exhibited a robust performance even when trained on small datasets, providing an approach for practitioners to conduct spam detection when the available data is inadequate.  ...  In this paper, we will show how various sets of online review features add value to the final performance of our proposed framework, as well as how different machine learning models perform regarding detecting  ...  The authors would also like to thank Professor Adam Meyers from New York University, whose teaching in Natural Language Processing motivated this work.  ... 
doi:10.18178/ijmlc.2021.11.1.1017 fatcat:2yodj3332zaebjrf7iwcaysvqy

Predicting the Industry of Users on Social Media [article]

Konstantinos Pappas, Rada Mihalcea
2016 arXiv   pre-print
We frame this task as classification using both feature engineering and ensemble learning.  ...  Automatic profiling of social media users is an important task for supporting a multitude of downstream applications.  ...  There exists a myriad research that analyzes language in order to profile social media users.  ... 
arXiv:1612.08205v1 fatcat:rf5ybj6trzbefopxbodeyh5aey

Catching them red-handed: Real-time Aggression Detection on Social Media

Herodotos Herodotou, Despoina Chatzakou, Nicolas Kourtellis
2020 Zenodo  
Aggression on social media has evolved into a major point of concern.  ...  However, recently proposed machine learning (ML) approaches to detect various types of aggressive behavior fall short, due to the fast and increasing pace of content gener- ation as well as evolution of  ...  The paper reflects only the authors' views and the Commission is not responsible for any use that may be made of the information it contains.  ... 
doi:10.5281/zenodo.4720556 fatcat:z76wzfmwa5c5fe2j6oxyeh2cai

Explainable Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media [article]

Hamad Zogan, Imran Razzak, Xianzhi Wang, Shoaib Jameel, Guandong Xu
2021 arXiv   pre-print
We also show that our model helps improve predictive performance when detecting depression in users who are posting messages publicly on social media.  ...  In this work, we propose interpretive Multi-Modal Depression Detection with Hierarchical Attention Network MDHAN, for detection depressed users on social media and explain the model prediction.  ...  ., [48] study the problem of early detection of depression from social media using deep learning where the leverage different word embeddings in an ensemble-based learning setup.  ... 
arXiv:2007.02847v2 fatcat:4y4xl7rysfdqtfj3pojqxk6zo4

Discovering Location Information in Social Media

Fred Morstatter, Huiji Gao, Huan Liu
2015 IEEE Data Engineering Bulletin  
Finally, we discuss how machine learning techniques can be applied to infer the location of a social media post, bringing this analysis to any message posted on social media.  ...  Social media is immensely popular, with billions of users across various platform.  ...  as it unfolds on social media.  ... 
dblp:journals/debu/MorstatterGL15 fatcat:3navv55lszd6vbw5g7khton6t4
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