The Perception of the Syrian Asylum Seekers in Turkey: Sentiment Analysis with Twitter Data

Abstract

This study examines the perception of Syrian refugees who have migrated to Turkey within the Turkish public. For this purpose, the reasons for Syrian refugees’ migration to Turkey, their population in Turkey, their distribution in Turkey, their education status and enrollment rates, their working lives, their impact on the economy, the aid provided to them, their impact on public services and security in Turkey were investigated. Subsequently, sentiment analyses were conducted based on machine learning approaches on Twitter to measure the perception of the Turkish public regarding Syrian refugees. Perception was examined in three different dimensions: general perception, the nature of perception, and the reasons behind perception. In this context, tweets related to Syrian refugees posted throughout the year 2021 were collected, pre-processed, and transformed into a format suitable for data mining algorithms. Some of the tweets were manually classified according to the machine learning technique, and the remaining tweets were automatically classified by algorithms determined, taking into account the manually made classifications. As a result, it was determined that the general perception of the Turkish public regarding Syrian refugees on Twitter is largely negative and characterized by ‘discontent’. The main reasons behind this perception were found to be the perceived harm caused by Syrian refugees, their high numbers, and perceptions that they are better off than the locals, primarily due to their refugee and residency rights.

Keywords

• asylum seekers
• turkey
• sentiment analysis
• machine learning
• twitter
• perception
• immigration
• economy
• public services
• security