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عنوان فارسی مقاله:
چارچوبی برای زمان واقعی تجزیه و تحلیل داده های توییتر
عنوان انگلیسی مقاله:
A framework for real-time Twitter data analysis
سال انتشار : 2015
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مقدمه انگلیسی مقاله:
1. Introduction
Over the last 40 years, providing automatic solutions to analyze text documents collection has been one of the most attractive challenges in the field of information retrieval. More recently, the focus has moved towards dynamic, distributed environments, where documents are continuously created by the users of a virtual community, i.e. the social network. In the case of Twitter, such text portions, called tweets, are usually related to events which involve many people in different parts of the world. In this paper we present a framework to analyze the Twitter stream in order to detect relevant topics within a generic macro event. Differently from other techniques which focus on the detection of specific events, e.g. earthquakes, or provide offline solutions for the analysis of tweets that match some static filter, our system has been designed to adapt its behavior to the specific nature of incoming data. After choosing some generic terms to query Twitter, the stream of tweets is split into dynamics windows which are analyzed to promptly detect relevant topics. Since our aim is to capture the user’s perspective on discussing the events, the initial set of keywords is progressively updated to include new important terms emerging from the tweets, or to delete those unused. The topic detection algorithm we present is an improved version of Soft Frequent Pattern Mining (SFPM), designed to overcome the limitations of SFPM in dealing with dynamic, real-time, detection scenarios. We chose SFPM as core of our framework for two reasons. First, because of its better performance in detecting relevant topics as compared to other basic techniques [1]; second, because of its modular design, which allows to easily change the way relevant terms are selected, while maintaining the efficiency of a simplified Frequent Pattern Mining approach.
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کلمات کلیدی:
Real-time Twitter sentiment analysis with Azure Stream Analytics ... https://docs.microsoft.com/...analytics/stream-analytics-twitter-sentiment-analysis-tren... Mar 28, 2017 - Learn how to use Stream Analytics for real-time Twitter sentiment analysis. Step-by-step guidance from event generation to data on a live ... A framework for real-time Twitter data analysis - Google Scholar https://scholar.google.it/citations?view_op=view_citation&hl=it... A description for this result is not available because of this site's robots.txt Learn more A Framework for Real-Time Twitter Data Analysis (PDF Download ... https://www.researchgate.net/.../282446443_A_Framework_for_Real-Time_Twitter_Dat... In this work we present a system for real-time Twitter data analysis in order to follow popular events from the user's perspective. The method we propose extends ... A survey on real-time event detection from the Twitter data stream ... journals.sagepub.com/doi/abs/10.1177/0165551517698564 by M Hasan Mar 17, 2017 - A survey on real-time event detection from the Twitter data stream .... Re GL, Morana M. A framework for real-time Twitter data analysis. Comput ... developing a real-time data analytics framework for twitter streaming ... thescholarship.ecu.edu/handle/10342/6045 by B Yadranjiaghdam - 2016 Dec 13, 2016 - Twitter is an online social networking service with more than 300 million users, generating a huge amount of information every day. Twitter's ... A Framework for Real-time Semantic Social Media Analysis www.semantic-web-journal.net/system/files/swj1271.pdf by D Maynard - Related articles Keywords: social media analysis, linked open data, semantic annotation, sentiment analysis, NLP. 1. .... of long-term Twitter monitoring and (near)-real time. Apache Storm storm.apache.org/ Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. ... Storm has many use cases: realtime analytics, online machine learning, ... Tweets · and many others ...
