TwiFly: A Data Analysis Framework for Twitter

被引：3

作者：

Chatziadam, Panagiotis ^{[1
]}

Dimitriadis, Aftantil ^{[1
]}

Gikas, Stefanos ^{[1
]}

Logothetis, Ilias ^{[1
]}

Michalodimitrakis, Manolis ^{[1
]}

Neratzoulakis, Manolis ^{[1
]}

Papadakis, Alexandros ^{[1
]}

Kontoulis, Vasileios ^{[1
]}

Siganos, Nikolaos ^{[1
]}

Theodoropoulos, Dimitrios ^{[1
]}

Vougioukalos, Giannis ^{[1
]}

Hatzakis, Ilias ^{[2
]}

Gerakis, George ^{[1
]}

Papadakis, Nikolaos ^{[1
]}

Kondylakis, Haridimos ^{[1
,3
]}

机构：

[1] Hellen Mediterranean Univ, Dept Elect & Comp Engn, GR-70013 Iraklion, Greece

[2] Hellen Mediterranean Univ, Dept Agr, GR-70013 Iraklion, Greece

[3] FORTH ICS, GR-70013 Iraklion, Greece

来源：

INFORMATION | 2020年 / 11卷 / 05期

关键词：

Twitter; political analysis; data analysis; EVENT DETECTION; TOOL;

D O I：

10.3390/info11050247

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Over the last decade, there have been many changes in the field of political analysis at a global level. Through social networking platforms, millions of people have the opportunity to express their opinion and capture their thoughts at any time, leaving their digital footprint. As such, massive datasets are now available, which can be used by analysts to gain useful insights on the current political climate and identify political tendencies. In this paper, we present TwiFly, a framework built for analyzing Twitter data. TwiFly accepts a number of accounts to be monitored for a specific time-frame and visualizes in real time useful extracted information. As a proof of concept, we present the application of our platform to the most recent elections of Greece, gaining useful insights on the election results.

引用

页数：14

共 50 条

[1] A FRAMEWORK FOR MASSIVE TWITTER DATA EXTRACTION AND ANALYSIS
AlvaroCuesta
Barrero, David F.
R-Moreno, Maria D.
[J]. MALAYSIAN JOURNAL OF COMPUTER SCIENCE, 2014, 27 (01) : 50 - 67
[2] HiSAT: Hierarchical Framework for Sentiment Analysis on Twitter Data
Kommu, Amrutha
Patel, Snehal
Derosa, Sebastian
Wang, Jiayin
Varde, Aparna S.
[J]. INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1, 2023, 542 : 376 - 392
[3] A framework for real-time Twitter data analysis
Gaglio, Salvatore
Lo Re, Giuseppe
Morana, Marco
[J]. COMPUTER COMMUNICATIONS, 2016, 73 : 236 - 242
[4] Sentiment Analysis Framework of Twitter Data Using Classification
Khurana, Medha
Gulati, Anurag
Singh, Saurabh
[J]. 2018 FIFTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING (IEEE PDGC), 2018, : 459 - 464
[5] Sentiment Analysis on Twitter Data using Apache Spark Framework
Elzayady, Hossam
Badran, Khaled M.
Salama, Gouda I.
[J]. PROCEEDINGS OF 2018 13TH INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND SYSTEMS (ICCES), 2018, : 171 - 176
[6] An Anomaly Detection Framework for Twitter Data
Kumar, Sandeep
Khan, Muhammad Badruddin
Abul Hasanat, Mozaherul Hoque
Saudagar, Abdul Khader Jilani
AlTameem, Abdullah
AlKhathami, Mohammed
[J]. APPLIED SCIENCES-BASEL, 2022, 12 (21):
[7] Sentiment Analysis of Big Data Applications using Twitter Data with the Help of HADOOP Framework
Sehgal, Divya
Agarwal, Ambuj Kumar
[J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON SYSTEM MODELING & ADVANCEMENT IN RESEARCH TRENDS (SMART-2016), 2016, : 251 - 255
[8] DATA ANALYSIS OF TWITTER DATA
Kasprikova, Nikola
[J]. 13TH INTERNATIONAL DAYS OF STATISTICS AND ECONOMICS, 2019, : 678 - 686
[9] A framework for intelligent Twitter data analysis with non-negative matrix factorization
Casalino, Gabriella
Castiello, Ciro
Del Buono, Nicoletta
Mencar, Corrado
[J]. INTERNATIONAL JOURNAL OF WEB INFORMATION SYSTEMS, 2018, 14 (03) : 334 - 356
[10] A polarity analysis framework for Twitter messages
Lima, Ana Carolina E. S.
de Castro, Leandro Nunes
Corchado, Juan M.
[J]. APPLIED MATHEMATICS AND COMPUTATION, 2015, 270 : 756 - 767

← 1 2 3 4 5 →