Muhammad Tafakur, Alvanov Zpalanzani

The Understanding Visual Language in Palestine-Israel conflict humanitarian Crowdfunding Campaigns:

Introduction

The understanding visual language in palestine-israel conflict humanitarian crowdfunding campaigns:. Explore visual language in Palestine-Israel conflict humanitarian crowdfunding. This study uses AWS Rekognition to ethically enhance donor empathy & campaign success, highlighting ML's role.

Abstract

Indonesia is widely acknowledged for its significant generosity globally, rooted deeply in cultural inclinations towards charitable activities and donations. This study explores the role of visual language in humanitarian crowdfunding campaigns, focusing on the Palestine-Israel conflict, and highlights the pivotal role of machine learning, specifically AWS Rekognition and Digital Content Analysis, in enhancing these campaigns. It categorizes campaign images into classifications such as superior fundraising activities, success levels, and degrees of poverty porn, leveraging demographic factors and thematic content to enhance campaign effectiveness. The study emphasizes how machine learning facilitates strategic deployment of visual elements—such as optimized shot composition, scale variations, and naturalistic portrayals—to ethically enhance viewer empathy and perception. Insights aim to deepen understanding of machine learning’s crucial role in shaping donor behavior and campaign success, proposing future directions in refining algorithms and ethical guidelines for impactful visual representation in humanitarian contexts. Keywords: Visual Language, Humanitarian Fundraising, AWS Rekognition, Poverty Porn, Digital content Analysist.  

Review

This study embarks on a timely and highly relevant exploration of visual language in humanitarian crowdfunding campaigns, particularly within the sensitive context of the Palestine-Israel conflict. Its innovative approach, integrating machine learning tools like AWS Rekognition and Digital Content Analysis, promises to offer significant advancements in understanding how visual elements influence donor behavior. By aiming to categorize campaign images based on fundraising success and the nuanced concept of "poverty porn," the research positions itself to provide valuable insights into optimizing visual strategies while also addressing critical ethical considerations in humanitarian appeals. The focus on leveraging Indonesia's philanthropic culture as a backdrop further enriches the potential for practical and culturally sensitive recommendations. A key strength of this abstract lies in its ambitious methodological framework, bridging social science insights with cutting-edge computational techniques. The proposed use of AWS Rekognition for image classification, coupled with an analysis of demographic factors and thematic content, suggests a rigorous attempt to move beyond qualitative assessments of visual impact. The explicit mention of categorizing images into "superior fundraising activities" and identifying "degrees of poverty porn" indicates a proactive engagement with both campaign effectiveness and ethical responsibility. This detailed analytical approach, emphasizing shot composition, scale, and naturalistic portrayals, has the potential to unpack the complex interplay between visual cues and donor empathy, thereby enhancing the strategic deployment of visual assets in a humanitarian context. While the abstract outlines a promising research agenda, some areas could benefit from further clarification in the full manuscript. For instance, the operationalization of "superior fundraising activities," "success levels," and especially "degrees of poverty porn" needs robust methodological definition. Understanding the specific criteria and metrics used for these categorizations will be crucial for replicability and validity. Furthermore, while the study's focus on Indonesia's generosity is noted, the precise scope and characteristics of the dataset (e.g., number of campaigns, types of platforms, and the specific connection to the Palestine-Israel conflict beyond being a context) would strengthen the proposal. Expanding on the proposed "future directions in refining algorithms and ethical guidelines" with concrete examples of how these might look in practice would also add substantial value.

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