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Few are as Good as Many: An Ontology-Based Tweet Spam Detection Approach
2018
IEEE Access
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To address the aforementioned challenges, we propose a novel ontology-based approach for spam detection over Twitter during events by analyzing the relationship between ham user tweets versus spams. ...
INDEX TERMS Twitter, meta-data, spam detection, text based analysis, event spammers, ontology. 63890 2169-3536 ...
relationship based information in order to discover spam • Reduces the need for a high similarity overlap while comparing tweets to ontologies by exploring the fact that few are as good as many terms, ...
doi:10.1109/access.2018.2877685
fatcat:tkqo36qrm5h4xi2qfeaqfgfou4
Spam, a Digital Pollution and Ways to Eradicate It
2019
International Journal of Engineering and Advanced Technology
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This survey is thus mainly used to discuss and analyze the recent research that had been put forth regarding the spam detection in social media sites such as Twitter. ...
We then compared all the methods present in the papers to see which method or combination of methods could give the best result in detecting spam. ...
But all in all, the few are good as many approaches will work accurately [3] . ...
doi:10.35940/ijeat.b4107.129219
fatcat:uze7gfg3wrgjdmetvpuhzhl7p4
Cost-based heterogeneous learning framework for real-time spam detection in social networks with expert decisions
2021
IEEE Access
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proposed an approach to streamline the cyber assets planning process by using probabilistic ontologies [54] . ...
As there are many types of spam tweets, it is often impossible to detect them by relying on specific features. ...
doi:10.1109/access.2021.3098799
fatcat:x7bv5dhmc5geplrh4z6rpb76uq
Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions
[article]
2020
arXiv
pre-print
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According to WHO, uncontrolled conspiracy theories and propaganda are spreading faster than the COVID-19 pandemic itself, creating an infodemic and thus causing psychological panic, misleading medical ...
This paper presents a large-scale study based on data mined from Twitter. ...
We built an ontology of experts based on several dictionaries. ...
arXiv:2005.08820v1
fatcat:vzwmd5mwzjendeaq3vfol6yxw4
Coalmine: an experience in building a system for social media analytics
2012
Cyber Sensing 2012
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Finally, we describe our experiences looking for evidence of botnet command and control channels and examining patterns of SPAM in the Twitter dataset. ...
Searching, correlating, and understanding billions of individual posts is a significant technical problem; even the data from a single site such as Twitter can be difficult to manage. ...
COALMINE: SPAM RESULTS BASED ON BOTNET STUDY When performing our Botnet C2 Channel discovery case study, we noticed a high volume of identical Tweets from different accounts. ...
doi:10.1117/12.918933
fatcat:uol23by5p5hyzg7z27c3g6e3di
Rumour Detection Models & Tools for Social Networking Sites
2019
International Journal of Engineering and Advanced Technology
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Finally, an improved RDM model is proposed in Figure 2, efficiency of this proposed RDM models is improved by embedding of Pre-defined rumour rules, WordNet Ontology and NLP/machine learning approach giving ...
RDM are effectively used in detecting the rumours from social media platforms (Twitter, Linkedln, Instagram, WhatsApp, Weibo sena and others) with the help of bag of words and machine learning approaches ...
Rumour Types Many of rumour detection methods are categorized into three paradigms namely hand-crafted features based classification approaches, the propagation-based approaches and the neural networks ...
doi:10.35940/ijeat.b3465.129219
fatcat:oyapwqs4cnhtffk3bmxbw7wmxe
Predictive Analytics Using Social Big Data and Machine Learning
[chapter]
2021
Social Big Data Analytics
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2021 pre-print arXiv:2104.12591v1 fatcat:w5izxqgeeberzliav5b4v3xrey
Then, various predictive analytical algorithms are introduced with their usage in several important application and top-tier tools and APIs. ...
ever-increase in the quality and quantity of data generated from day-to-day businesses operations in conjunction with the continuously imported related social data have made the traditional statistical approaches ...
The approach has been applied effectively on text/opinion mining, spam detection, and decision recommendations. ...
doi:10.1007/978-981-33-6652-7_5
fatcat:m3hzovxp5fdrvbbunmuzwc6gby
Semantic analysis of offensive language categories from existing annotated corpora
2022
Uporabna informatika
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We use natural language processing techniques to find correlations between the categories based on seven different data sets. ...
The findings reveal that most of the categories are densely interconnected, while a two-level hierarchical representation of them can be provided. ...
[Bretschneider and Peters, 2016] use three human experts for the annotation and then propose an approach to precisely detect cyberbullies and also provide metrics to identify victims of severe cyberbullying ...
doi:10.31449/upinf.vol30.num1.151
fatcat:mrrny5ynznhlbek2ezr7g4fa4m
Ontology-driven aspect-based sentiment analysis classification: An infodemiological case study regarding infectious diseases in Latin America
2020
Future generations computer systems
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We intend to fill these gaps proposing an ontology-driven aspect-based sentiment analysis with which to measure the general public's opinions as regards infectious diseases when expressed in Spanish by ...
This new information is subsequently applied in order to build an aspect-based sentiment analysis model based on statistical and linguistic features. This is done by applying deep-learning models. ...
However, in order to maintain as many tweets as possible, we tried an alternative approach with two binary classifications. ...
doi:10.1016/j.future.2020.06.019
pmid:32572291
pmcid:PMC7301140
fatcat:xxt6mfojevf3zhpu4fchr3lzuq
A Survey on Sentimental Analysis Approaches using Machine Learning Algorithms
2022
International Journal for Research in Applied Science and Engineering Technology
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Some approaches which uses special statistical and machine learning models are included in separate section. ...
In this work, a survey has been conducted on various work done in the past on sentiment analysis which includes opinion mining methods, machine learning based approaches and hybrid approaches which combines ...
Next the instance-based approach for filtering the spams allows the sharing of instances with the effort of labeling e-mail as spam. ...
doi:10.22214/ijraset.2022.42005
fatcat:ss2f2lpznzcktakldpbete3evu
Modeling and Evaluating Information Diffusion for Spam Detection in Micro-blogging Networks
2015
KSII Transactions on Internet and Information Systems
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Besides, the non-spam posts always get their first reposts/comments much sooner than the spam posts. With the features defined in our model, we propose an RBF-based approach to detect spams. ...
Prior detection tools are either designed for specific types of spams or not robust enough. Spammers may escape easily from being detected by adjusting their behaviors. ...
Many detection approaches are based on link examination. ...
doi:10.3837/tiis.2015.08.014
fatcat:5lsd6uthxjc73jtqrraw4eryzu
Real-Time Social Network Data Mining for Predicting the Path for a Disaster
2016
Journal of Advances in Information Technology
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The steps involved in the framework are -data collection, data preprocessing, geolocating the tweets, data filtering and extrapolation of the disaster curve for prediction of susceptible locations. ...
The users of Twitter act as the sensors which provide useful information about the disaster by posting first-hand experience, warnings or location of a disaster. ...
They built an earthquake semantic network using human activity on Twitter based on Web Ontology Language. ...
doi:10.12720/jait.7.2.81-87
fatcat:vvyjz42z6rgqznfilw3fjeigk4
Credibility Analysis for Available Information Sources on the Web: A Review and a Contribution
2019
2019 4th International Conference on System Reliability and Safety (ICSRS)
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We show a proof of concepts through the development of World White Web, a Google Chrome extension application that implements the model to analyze tweets in real time, using web scraping. ...
There are many free and open source algorithms to detect SPAM that can be used to implement this isSP AM filter. ...
t.tex) = detect spam(t.text) where detect spam is an algorithm that analyzes t.text and returns the probability of t.text being a SPAM. ...
doi:10.1109/icsrs48664.2019.8987623
fatcat:bpn7cy4kangw5bdwetdskxpdp4
Processing Social Media Messages in Mass Emergency
2015
ACM Computing Surveys
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In this survey, we cover these various approaches, and highlight their benefits and shortcomings. ...
In particular, many social media messages communicated during emergencies convey timely, actionable information. ...
ACKNOWLEDGMENTS We are thankful to Jakob Rogstadius and Per Aarvik, who pointed us to historical information. ...
doi:10.1145/2771588
fatcat:fb6bypzs6zdqznxv4maltpxvqq
A framework for syntactic and semantic quality evaluation of ontologies
[article]
2021
arXiv
pre-print
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This paper proposes an ontology quality evaluation framework consisting of: (a) SynEvaluator and (b) SemValidator for evaluating syntactic and semantic aspects of ontologies respectively. ...
Current quality evaluation approaches oftentimes seek to evaluate ontologies in either syntactic (degree of following ontology development guidelines) or semantic (degree of semantic validity of enriched ...
In the past few years, a good number of crowdsourced ontology evaluation approaches
have been proposed. ...
arXiv:2112.08543v1
fatcat:5l4h42ymura57ittm5me74ho44
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