The study aimes to analyze the discourse of Arab tweeters regarding the normalization of Arab-Israeli relations on the social media site (Twitter).
Study Methodology: The study relay on the survey method, using the comprehensive survey method, and this research is one of the descriptive types that aim to describe the phenomenon in a qualitative way, and discuss it through the method of in-depth analysis, in addition to using the tools of (discourse analysis).
Study sample: A sample of (8686) tweets for (7425) tweeters, which was posted on Twitter during the period from 15/9 to 30/9/2020, on the issue of normalizing Arab-Israeli relations.
Study tools: The data study was collected using the data mining tool from social networks (NodeXL), along with a discourse analysis sheet.
The most prominent results of the study:
The thesis (popular rejection of normalization with Israel) rank first for the theses addressed in the tweets. The negative features attributed to the active forces in the Arab countries focused on their official position in support and defender of normalization. As for the positive features, the role and popular position rejecting normalization were shared. The frameworks of the case focused on the framework of Palestinian reconciliation, the framework of the US-Iranian conflict in the Middle East, and the framework of the conflict within the ruling regimes regarding normalization. While the personality framework focused on Palestinian martyrs, Arab presidents and rulers who support normalization, as well as clerics. The causes and consequences were varied in their content.
The study of services in villages is one of the imperative matters that must be focused on, because it leads to increased attention, which reduces the differences between the countryside and the urban. The extent of its.
It is well known that community services need to be reached by a person, unlike the anchor services that reach people, here the population distribution plays an important and prominent role in signing these services, so the dispersed distribution pattern and the gathering pattern appeared in the distribution, thus an effect on the time and distance that the person walked to obtain The services are community-based. Therefore
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