Social Media Analysis based on Semanticity of Streaming and Batch Data
Languages shared by people differ in different regions based on their accents, pronunciation and word usages. In this era sharing of language takes place mainly through social media and blogs. Every second swing of such a micro posts exist which induces the need of processing those micro posts, in-order to extract knowledge out of it. Knowledge extraction differs with respect to the application in which the research on cognitive science fed the necessities for the same. This work further moves forward such a research by extracting semantic information of streaming and batch data in applications like Named Entity Recognition and Author Profiling. In the case of Named Entity Recognition context of a single micro post has been utilized and context that lies in the pool of micro posts were utilized to identify the sociolect aspects of the author of those micro posts. In this work Conditional Random Field has been utilized to do the entity recognition and a novel approach has been proposed to find the sociolect aspects of the author (Gender, Age group).
Code (0)
등록된 구현이 없습니다.
Tasks
Author Profilingnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Similar Papers 제목 키워드 기반
A Streaming Machine Learning Framework for Online Aggression Detection on Twitter
The rise of online aggression on social media is evolving into a major point of concern. Several machine and deep learning approaches have been proposed recently for detecting various types of aggressive behavior. Howeve…
BIG-bench Machine LearningExploratory Analysis for Ontology Learning from Social Events on Social Media Streaming in Spanish
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis
When an agent acquires new information, ideally it would immediately be capable of using that information to understand its environment. This is not possible using conventional deep neural networks, which suffer from cat…
BIG-bench Machine Learningclass-incremental learningClass Incremental LearningAlertMix: A Big Data platform for multi-source streaming data
The demand for stream processing is increasing at an unprecedented rate. Big data is no longer limited to processing of big volumes of data. In most real-world scenarios, the need for processing stream data as it comes c…
Fraud DetectionDetecting and Summarizing Emergent Events in Microblogs and Social Media Streams by Dynamic Centralities
Methods for detecting and summarizing emergent keywords have been extensively studied since social media and microblogging activities have started to play an important role in data analysis and decision making. We presen…
Decision Making