Citation: Sufi, F.; Alsulami, M. A
Novel Method of Generating
Geospatial Intelligence from Social
Media Posts of Political Leaders.
Information 2022, 13, 120. https://
doi.org/10.3390/info13030120
Academic Editor: Louai Alarabi
Received: 9 February 2022
Accepted: 25 February 2022
Published: 28 February 2022
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information
Article
A Novel Method of Generating Geospatial Intelligence from
Social Media Posts of Political Leaders
Fahim Sufi
1,
* and Musleh Alsulami
2
1
Independent Researcher, Melbourne, VIC 3000, Australia
2
Information Systems Department, Umm Al-Qura University (UQU), Makkah 24382, Saudi Arabia;
mhsulami@uqu.edu.sa
* Correspondence: research@fahimsufi.com
Abstract: Social media platforms such as Twitter have been used by political leaders, heads of
states, political parties, and their supporters to strategically influence public opinions. Leaders can
post about a location, a state, a country, or even a region in their social media accounts, and the
posts can immediately be viewed and reacted to by millions of their followers. The effect of social
media posts by political leaders could be automatically measured by extracting, analyzing, and
producing real-time geospatial intelligence for social scientists and researchers. This paper proposed
a novel approach in automatically processing real-time social media messages of political leaders
with artificial intelligence (AI)-based language detection, translation, sentiment analysis, and named
entity recognition (NER). This method automatically generates geospatial and location intelligence
on both ESRI ArcGIS Maps and Microsoft Bing Maps. The proposed system was deployed from 1
January 2020 to 6 February 2022 to analyze 1.5 million tweets. During this 25-month period, 95K
locations were successfully identified and mapped using data of 271,885 Twitter handles. With an
overall 90% precision, recall, and F
1
score, along with 97% accuracy, the proposed system reports the
most accurate system to produce geospatial intelligence directly from live Twitter feeds of political
leaders with AI.
Keywords: sentiment analysis on political tweets; named entity recognition on political tweets;
geospatial intelligence; analyzing tweets of political leaders; big data processing of social media
1. Introduction
As of July 2021, 5.2 billion people have access to the internet, representing 65% of
the global population [1]. Many of these people have access to social media and are
constantly posting updates on their social media accounts. Hence, in every minute Facebook
users share 240,000 photos, Facebook live receives 44,000,000 views, Instagram users
share 65,000 photos, YouTube users stream 694,000 h of videos, Snapchat users send
2,000,000 Snapchats, and Twitter users post 575,000 tweets, generating a massive volume
of big data [1]. A study in 2020 found that there are 1089 active Twitter accounts of heads
of states, ministers, diplomats, and political leaders out of which 632 have been verified
by Twitter [2]. Derogatory remarks in social media by political leaders are reacted to and
retweeted since the public is drawn to negative events and news reports [3]. For example,
A tweet by Donald Trump at 9:43 p.m. on 20 July 2020 states, “We are united in our effort
to defeat the invisible China virus, and many people say that it is patriotic to wear a face
mask when you can’t socially distance. There is nobody more patriotic than me, your
favorite president” [2]. This tweet almost instantly reached 20 million or 23% of the total
followers (i.e., 88 million) of Donald Trump [2]. From then, the followers retweeted, reacted,
and shared this view, creating a global impact on the country mentioned within the tweet.
Measuring the impact of social media posts on a particular nation, country, or state is
significant for any nation since diplomatic ties and geopolitical situations are severely
affected by derogatory and negative posts by political leaders. Even though there has been
Information 2022, 13, 120. https://doi.org/10.3390/info13030120 https://www.mdpi.com/journal/information