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		<title>AI Sentiment Analysis Alone Cannot Tell Truth From Health Misinformation, Major Review Finds</title>
		<link>https://bioengineer.org/ai-sentiment-analysis-alone-cannot-tell-truth-from-health-misinformation-major-review-finds/</link>
		
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		<pubDate>Fri, 16 Oct 2026 19:14:06 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[AI ethics]]></category>
		<category><![CDATA[big data analytics]]></category>
		<category><![CDATA[data quality]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[Frontiers in Big Data]]></category>
		<category><![CDATA[health misinformation]]></category>
		<category><![CDATA[human verification]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[public health surveillance]]></category>
		<category><![CDATA[real-time analytics]]></category>
		<category><![CDATA[sentiment analysis]]></category>
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					<description><![CDATA[A systematic review of thirty studies finds that sentiment analysis can flag emotional tone in health content but cannot determine factual accuracy, and that data quality, human verification, and governance matter as much as advanced AI models.]]></description>
		
		
		
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		<title>How We Measure Recommenders Matters: Rethinking Evaluation for Real-World Search and Recommendation</title>
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		<pubDate>Fri, 16 Oct 2026 18:50:22 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[algorithmic fairness]]></category>
		<category><![CDATA[career path prediction]]></category>
		<category><![CDATA[comment moderation]]></category>
		<category><![CDATA[evaluation]]></category>
		<category><![CDATA[Frontiers in Big Data]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[LLM-as-a-judge]]></category>
		<category><![CDATA[recommender systems]]></category>
		<category><![CDATA[search systems]]></category>
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					<description><![CDATA[A new Frontiers in Big Data editorial argues that recommender and search systems must be evaluated with robust, responsible and stakeholder-aware methods that go beyond static benchmarks.]]></description>
		
		
		
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