Big data emerging technologies: A CaseStudy with analyzing twitter data using apache hive

Bhardwaj, Aditya; Vanraj,; Kumar, Ankit; Narayan, Yogendra; Kumar, Pawan

doi:10.1109/raecs.2015.7453400

Cited by 25 publications

(13 citation statements)

References 32 publications

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“…Flume agent has three components and they are the source, channel and sink. The source collects the events to the agent, the channel acts as a buffer that store data from source before writing into the HDFS, and sinks is responsible to store the data to HDFS [10]. It dumps data in HDFS in different formats.…”

Section: Apache Flumementioning

confidence: 99%

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Twitter data analysis using hadoop ecosystems and apache zeppelin

Wilson

Sivakumar

2019

IJEECS

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The day-to-day life of the people doesn't depend only on what they think, but it is affected and influenced by what others think. The advertisements and campaigns of the favourite celebrities and mesmerizing personalities influence the way people think and see the world. People get the news and information at lightning speed than ever before. The growth of textual data on the internet is very fast. People express themselves in various ways on the web every minute. They make use of various platforms to share their views and opinions. A huge amount of data is being generated at every moment on this process. Being one of the most important and well-known social media of the present time, millions of tweets are posted on Twitter every day. These tweets are a source of very important information and it can be made use for business, small industries, creating government policies, and various studies can be performed by using it. This paper focuses on the location from where the tweets are posted and the language in which the tweets are written. These details can be effectively analysed by using Hadoop. Hadoop is a tool that is used to analyze distributed big data, streaming data, timestamp data and text data. With the help of Apache Flume, the tweets can be collected from Twitter and then sink in the HDFS (Hadoop Distributed File System). These raw data then analyzed using Apache Pig and the information available can be made use for social and commercial purposes. The result will be visualized using Apache Zeppelin.

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Section: Apache Flumementioning

confidence: 99%

“…The paper [10] elaborately looks into the emerging technologies in the field of big data. It takes Twitter as a source for big data and discusses various analysing possibilities with Hadoop ecosystems.…”

Section: Literature Reviewmentioning

confidence: 99%

Twitter data analysis using hadoop ecosystems and apache zeppelin

Wilson

Sivakumar

2019

IJEECS

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“…Aditya Bhardwaj and Ankit kumar(2015) [1] have talked about on enormous information examination. As showed by them, Hadoop defines to the bulk of information past customary database innovation ability to store, get to, oversee then register proficiently.…”

Section: Related Workmentioning

confidence: 99%

An efficient approach to predict emergency calls and locations

Narayana¹,

Venkatesh²,

Mourya³

et al. 2018

IJET

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Big data stands for huge set or collecting information which can't be prepared by modern techniques, for example, data processing. Exmining enormous information has the quality in the arena of interpersonal organizations, spot business patterns, web, drug, science, fund, commerce informatics and indeed in government. Dissecting information would assistance in extraordinary basic leadership, which may achieve change happening productivity, diminishment in cost and disappointment dangers. Enormous information examination turns into an awesome hunger for the creating associations since it winds up plainly troublesome for those associations to process a excess of tera bytes of information. Huge information investigation even discovers its request in considerate the purpose behind regular or man influenced failures by gathering enormous information keeping in observance conclusion to recuperate from the catastrophe and to develop the correspondence since correspondence is the primary test that the common people face while confronting sudden failures..

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“…The Streaming API works by making a request for a specific type of data which is filtered by keyword, a user, geographic area etc. [2] Once connection to the Twitter API is established via the Streaming API, data collection takes place. The tweets collected will be encoded in JavaScript Object Notation (JSON).…”

Section: Data From Twittermentioning

confidence: 99%

Opinion Mining of Twitter Data using Hive

Kirar¹,

Sain²,

Shrivastava³

2016

IJCA

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In todays extremely developed world, each minute, individuals round the globe specific themselves via numerous platforms on the net. And in every minute, an enormous quantity of unstructured information is generated. This information is within the style of text that is gathered from forums and social media websites. Such information is termed as massive information. User opinions square measure associated with a good vary of topics like politics, latest gadgets and merchandise. Social Networking sites provides tremendous impetus for large information in mining people's opinion. Public API's catered by sites like Twitter provides North American nation with helpful information for studying writer's perspective in terms of of a specific topic, product etc. To distinguish people's opinion, tweets square measure labeled into positive, negative or neutral indicators. This paper provides an efficient mechanism to perform opinion mining by coming up with a finish to finish pipeline with the assistance of Apache Flume ,Apache HDFS, and Apache Hive. Here we proposed to develop a opinion Analysis mechanism to analyze the various polarity of opinions of Twitter users through their tweets in order to extract what they think. Here we have used dictionary based approach for analysis for which we have implemented hive queries through which we can analysis these complex twitter data to check polarity of the tweets based on the polarity dictionary through which we can say that which tweets have negative opinion or positive opinion.

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Big data emerging technologies: A CaseStudy with analyzing twitter data using apache hive

Cited by 25 publications

References 32 publications

Twitter data analysis using hadoop ecosystems and apache zeppelin

Twitter data analysis using hadoop ecosystems and apache zeppelin

An efficient approach to predict emergency calls and locations

Opinion Mining of Twitter Data using Hive

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