Using Social Media Data to Map Mortar Shells Falling in Damascus, Syria

DOI: 10.35595/2414-9179-2021-2-27-233-240

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Об авторе

Mohamad Hasan

Saint Petersburg University,
Sredniy prospekt V.O., 41, 199034, Saint-Petersburg, Russia;


The paper analyzes the use of social media data in geographical information systems to map the areas most affected by mortar shells in the capital of Syria, Damascus, by using geocoded and parsed social media data in geographical information systems. This paper describes a created algorithm to collecting and store data from social media sites. For the data store both a NoSQL database to save JSON format document and an RDBMS is used to save other spatial data types. A python script was written to collect the data in social media based on certain keywords related to the search. A geocoding algorithm to locate social media posts that normalize, standardize and tokenize the text was developed. The result of the developed diagram provided a year by year from 2013 to 2018 maps for mortar shell falling locations in Damascus. These layers give an overview for the changing of the numbers of mortar shells falls or in hot spot analysis for the city. Finally, social media data can prove to be useful when creating maps for dynamic social phenomena, for example, mortar shells’ location falling in Damascus, Syria. Moreover, social media data provide easy, massive, and timestamped data which makes these phenomena easier to study.

Ключ. слова

data mining, geocoding, NoSQL databases, social media

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Для цитирования: Hasan M. Using Social Media Data to Map Mortar Shells Falling in Damascus, Syria. ИнтерКарто. ИнтерГИС. Геоинформационное обеспечение устойчивого развития территорий: Материалы Междунар. конф. M: Географический факультет МГУ, 2021. Т. 27. Ч. 2. С. 233–240 DOI: 10.35595/2414-9179-2021-2-27-233-240

For citation: Hasan M. Using Social Media Data to Map Mortar Shells Falling in Damascus, Syria. InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2021. V. 27. Part 2. P. 233–240. DOI: 10.35595/2414-9179-2021-2-27-233-240