Proposing a Model for Analyzing Textual Feedback from Users on Social Networks Facing Environmental Events and Actions

Authors
1 University of Tehran Kish International Campus
2 University of Tehran
Abstract
Background and Objective: The study aims to develop and validate a model for analyzing the textual feedback of users in social networks in the face of environmental events and actions with emphasis on identifying the factors affecting the presentation of text messages by users in social networks.

Research Methodology: Heuristic mixed method has been used. In the first stage, the meta-combined method was applied with a qualitative basis. In the second stage, to inspect, validate the identified factors and prepare the final research model, the survey method via questionnaire and forming conveyor group was combined. Population consisted of: 1) Selection and analysis of written documents related to the analysis of textual feedback and users' feelings, including 60 articles and works based on valid criteria from among 198 articles and works; 2) Experts in information technology, sociology, behaviorism, etc., which 15 people were selected, but as a result and limitations of the corona pandemic comments and suggestions were remotely submitted.

Results: Using the seven steps of meta-combination, a conceptual pattern was obtained in six conceptual layers, categories and codes. In each layer, concepts and topics were included, and to end 27 components were identified. For qualitative validation, the obtained model was found based on the opinions of experts in the form of focus groups and the conceptual model was approved by the research experts.

Conclusion: The conceptual model - obtained from the hybrid stages and focus groups – which has been approved and accepted by experts could be used as a basis for future research to guide, and direct the behavior of users in social networking in order to provide strategies and executive policies for officials and decision makers in relevant organizations and institutions.
Keywords

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