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

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