Filters








26 Hits in 6.5 sec

Mining Social Media for Newsgathering: A Review [article]

Arkaitz Zubiaga
2019 arXiv   pre-print
In this paper, we provide an overview of research in data mining and natural language processing for mining social media for newsgathering.  ...  This is in part possible thanks to the existence of mobile devices, which allows anyone with access to the Internet to post updates from anywhere, leading in turn to a growing presence of citizen journalism  ...  ; (2) exploiting information that same-topic tweets should also be similar in terms of credibility; and (3) use of a semi-supervised learning scheme that leverages the decisions of two independent credibility  ... 
arXiv:1804.03540v2 fatcat:s4ia7c5hfjbvzp3nxjiicnnfde

Learning User Embeddings from Temporal Social Media Data: A Survey [article]

Fatema Hasan, Kevin S. Xu, James R. Foulds, Shimei Pan
2021 arXiv   pre-print
The temporal nature of user-generated data on social media has largely been overlooked in much of the existing user embedding literature.  ...  We categorize relevant papers along several key dimensions, identify limitations in the current work and suggest future research directions.  ...  User-specific marked multivariate Hawkes processes were used by [Khodadadi et al., 2018] to model questions and answers on Stack Overflow with marks denoting badges that users may earn.  ... 
arXiv:2105.07996v1 fatcat:6elhasieuzce5ogddsl7uukv64

Mining social media for newsgathering: A review

Arkaitz Zubiaga
2019 Online Social Networks and Media  
In this paper, we provide an overview of research in data mining and natural language processing for mining social media for newsgathering.  ...  This is in part possible thanks to the existence of mobile devices, which allows anyone with access to the Internet to post updates from anywhere, leading in turn to a growing presence of citizen journalism  ...  ; (2) exploiting information that same-topic tweets should also be similar in terms of credibility; and (3) use of a semi-supervised learning scheme that leverages the decisions of two independent credibility  ... 
doi:10.1016/j.osnem.2019.100049 fatcat:dt63zddmqba7vc47cyjve37i5q

Predictive Analysis on Twitter: Techniques and Applications [article]

Ugur Kursuncu, Manas Gaur, Usha Lokala, Krishnaprasad Thirunarayan, Amit Sheth, I. Budak Arpinar
2018 arXiv   pre-print
In this chapter, we discuss techniques, approaches and state-of-the-art applications of predictive analysis of Twitter data.  ...  Specifically, we present fine-grained analysis involving aspects such as sentiment, emotion, and the use of domain knowledge in the coarse-grained analysis of Twitter data for making decisions and taking  ...  A probabilistic topic model with a semi-supervised approach is developed to assess clinical depression symptoms.  ... 
arXiv:1806.02377v1 fatcat:gm5cqpmgvfggzgxgzocv4c3fqi

Predictive Analysis on Twitter: Techniques and Applications [chapter]

Ugur Kursuncu, Manas Gaur, Usha Lokala, Krishnaprasad Thirunarayan, Amit Sheth, I. Budak Arpinar
2018 Lecture Notes in Social Networks  
In this chapter, we discuss techniques, approaches and state-of-the-art applications of predictive analysis of Twitter data.  ...  Specifically, we present fine-grained analysis involving aspects such as sentiment, emotion, and the use of domain knowledge in the coarse-grained analysis of Twitter data for making decisions and taking  ...  A probabilistic topic model with a semi-supervised approach is developed to assess clinical depression symptoms.  ... 
doi:10.1007/978-3-319-94105-9_4 fatcat:knquzcuqcjdjjguzq435nq5kni

Blackmarket-Driven Collusion on Online Media: A Survey

Hridoy Sankar Dutta, Tanmoy Chakraborty
2021 ACM/IMS Transactions on Data Science  
We believe that collusive entity detection is a newly emerging topic in anomaly detection and cyber-security research in general, and the current survey will provide readers with an easy-to-access and  ...  This survey is the first attempt to provide readers a comprehensive outline of the latest studies dealing with the identification and analysis of blackmarket-driven collusion in online media.  ...  [49] proposed HawkesEye, a classifier based on the Hawkes process and topic modeling to detect collusive retweeters on Twitter.  ... 
doi:10.1145/3517931 fatcat:7fvgujegh5hohdiemsok6kzviq

Learning Representations of Social Media Users [article]

Adrian Benton
2018 arXiv   pre-print
We then show how user features can be employed as distant supervision to improve topic model fit.  ...  Finally, we show how user features can be integrated into and improve existing classifiers in the multitask learning framework.  ...  Application: Predicting Policy Surveys with Twitter Data In section 4.2, we presented a new supervised topic model that is more resilient to noisy supervision than DMR.  ... 
arXiv:1812.00436v1 fatcat:qp2hf6f6nfe7djyjakkns36epq

Towards Understanding the Information Ecosystem Through the Lens of Multiple Web Communities [article]

Savvas Zannettou
2019 arXiv   pre-print
Our analysis reveal that fringe Web communities like 4chan's /pol/ and The_Donald subreddit have a disproportionate influence on mainstream communities like Twitter with regard to the dissemination of  ...  Yet, we lack tools and techniques to effectively track the propagation of information across the multiple diverse communities, and to model the interplay and influence between them.  ...  By designing and developing a scalable processing pipeline we were able to detect and track the propagation of memes across the Web.  ... 
arXiv:1911.10517v1 fatcat:piuwv7zv7zghlof5tqhuhnukla

Lifecycle Modeling for Buzz Temporal Pattern Discovery

Yi Chang, Makoto Yamada, Antonio Ortega, Yan Liu
2016 ACM Transactions on Knowledge Discovery from Data  
In social media analysis, one critical task is detecting a burst of topics or buzz, which is reflected by extremely frequent mentions of certain keywords in a short time interval.  ...  More specifically, we propose to model multiple peaks in buzz time-series with PLC mixture or PLC group mixture, and develop a probabilistic graphical model (K-MPLC ) to automatically discover inherent  ...  The views and conclusions are those of the authors and should not be interpreted as representing the official policies of the funding agency, or the U.S. Government.  ... 
doi:10.1145/2994605 fatcat:7qbytdz2xrgxxb5ayndu4blurq

Public vs media opinion on robots and their evolution over recent years

Alireza Javaheri, Navid Moghadamnejad, Hamidreza Keshavarz, Ehsan Javaheri, Chelsea Dobbins, Elaheh Momeni-Ortner, Reza Rawassizadeh
2020 CCF Transactions on Pervasive Computing and Interaction  
This paper investigates text corpora, consisting of posts in Google News, Bing News, and Kickstarter, over an 8-year period and Twitter over a 1-year period, to quantify the public's and media's opinion  ...  During recent years, the fast proliferation of robots in people's everyday lives calls for a profound examination of public consensus, which is the ultimate determinant of the future of this industry.  ...  This lexicon works based on WORDNET synsets. 11 The synsets of WORDNET are employed in SentiWordNet, which runs a semi-supervised text classification process in order to classify the synsets into groups  ... 
doi:10.1007/s42486-020-00035-1 fatcat:gwk3fo74abewfm4hvowt74pb6i

Artificial Intelligence for Social Good: A Survey [article]

Zheyuan Ryan Shi, Claire Wang, Fei Fang
2020 arXiv   pre-print
AI4SG has received lots of attention from the research community in the past decade with several successful applications.  ...  group the existing literature and analyze the eight AI4SG application domains in a unified framework. (3) We distill five research topics that represent the common challenges in AI4SG across various application  ...  Acknowledgments This work was supported in part by NSF grant IIS-1850477.  ... 
arXiv:2001.01818v1 fatcat:t6sn75k56nb3fbqi4vi52i2j44

Toylabs D2.1 - Toylabs Open Innovation And Co-Creation Integrated Methodology -V1

ToyLabs Consortium
2017 Zenodo  
gathering" and finally "Partner Matching", both from the perspective of the manufacturing industry in general but also zooming in the toy industry, in particular, to identify its state-of-the-art with  ...  The main purpose of this deliverable is to hand over a unified methodology, to be used by the toy industry, and specifically SMEs, for attaching more value to their design processes and new product development  ...  Typical topic detection methods that were identified during the literature review are being grouped in two categories; the application of probabilistic topic model algorithms and the application of feature  ... 
doi:10.5281/zenodo.1319400 fatcat:wj5neg4e5beu7bwksckqhwv25y

Aspect Level Public Opinion Detection, Tracking and Visualization on Social Media

Wanying Ding, Xiaohua Hu, Chaomei Chen
2017
We have proposed three statistical methods: Hybrid HDP-LDA Model, Similarity Dependency Dirichlet Process, and Semi-Supervised Dirichlet Process.  ...  Experiment results have confirmed their ability in unsupervised or semi-supervised opinion detection. Deep Learning frees people from feature engineering.  ...  They are Hybrid HDP-LDA model, Similarity Dependency Dirichlet Process model, and Semi-Supervised Dirichlet Process mode.  ... 
doi:10.17918/etd-7653 fatcat:hocicam6one2fe4lfvjegtrx5a

Contextual Search: A Computational Framework

Massimo Melucci
2012 Foundations and Trends in Information Retrieval  
The growing availability of data in electronic form, the expansion of the World Wide Web (WWW) and the accessibility of computational methods for large-scale data processing have allowed researchers in  ...  Therefore, in this survey, we describe how statistical models can process contextual variables to infer the contextual factors underlying the current search context.  ...  Sebastiani for inviting me to write this survey; Doug Oard for his great patience and encouragement; and three anonymous reviewers for their careful and thoughtful comments.  ... 
doi:10.1561/1500000023 fatcat:bjx5it7en5fapbg6fvbqs6e7jy

Learning User Embeddings from Temporal Social Media Data: A Survey [article]

Fatema Hasan, Kevin S. Xu, James R. Foulds, Shimei Pan, Maryland Shared Open Access Repository
2021
The temporal nature of user-generated data on social media has largely been overlooked in much of the existing user embedding literature.  ...  We categorize relevant papers along several key dimensions, identify limitations in the current work and suggest future research directions.  ...  User-specific marked multivariate Hawkes processes were used by [Khodadadi et al., 2018] to model questions and answers on Stack Overflow with marks denoting badges that users may earn.  ... 
doi:10.13016/m2wvcv-hbph fatcat:ohhf64nzh5fj7myk4dsnnfiqha
« Previous Showing results 1 — 15 out of 26 results