Social media data processing infrastructure by using Apache spark big data platform: Twitter data analysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F19%3A10244019" target="_blank" >RIV/61989100:27740/19:10244019 - isvavai.cz</a>

Result on the web

<a href="https://dl.acm.org/doi/10.1145/3361821.3361825" target="_blank" >https://dl.acm.org/doi/10.1145/3361821.3361825</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3361821.3361825" target="_blank" >10.1145/3361821.3361825</a>

Result language

angličtina

Original language name

Social media data processing infrastructure by using Apache spark big data platform: Twitter data analysis

Original language description

Social media provide continuous data streams that contain information with different level of sensitivity, validity and accuracy. Therefore, this type of information has to be properly filtered, extracted and processed to avoid noisy and inaccurate results. The main goal of this work is to propose architecture and workflow able to process Twitter social network data in near real-time. The primary design of the introduced modern architecture covers all processing aspects from data ingestion and storing to data processing and analysing. This paper presents Apache Spark and Hadoop implementation. The secondary objective is to analyse tweets with the defined topic - floods. The word frequency method (Word Clouds) is shown as a major tool to analyse the content of the input dataset. The experimental architecture confirmed the usefulness of many well-known functions of Spark and Hadoop in the social data domain. The platforms which were used provided effective tools for optimal data ingesting, storing as well as processing and analysing. Based on the analytical part, it was observed that the word frequency method (n-grams) can effectively reveal the tweets content. According to the results of this study, the tweets proved their high informative potential regarding data quality and quantity. (C) 2019 Association for Computing Machinery.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

CCIOT 2019 : September 20-22, 2019, Tokyo, Japan : 2019 4th International Conference on Cloud Computing and Internet of Things

ISBN

978-1-4503-7241-1

ISSN

—

e-ISSN

—

Number of pages

6

Pages from-to

1-6

Publisher name

Association for Computing Machinery

Place of publication

New York

Event location

Tokio

Event date

Sep 20, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—