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BrandTrustQuantification

tags: ReputationModeling, TrustIndices, SentimentAnalysis

Note: This is an AI-generated dataset so its content may be inaccurate or false

Dataset Description:

The 'BrandTrustQuantification' dataset is a curated collection of textual data derived from various sources such as customer reviews, social media posts, and brand communications. The dataset has been labeled to quantify the reputation and corporate social responsibility (CSR) of brands. It is intended to assist machine learning practitioners in training models for reputation modeling, trust indices, and sentiment analysis, focusing on CSR perceptions.

The dataset comprises text entries with an associated label that indicates the perceived brand reputation and CSR level based on the content. Labels are assigned based on predefined criteria that consider positive sentiment, references to ethical practices, and customer trust.

CSV Content Preview:

text,label
"This brand always goes above and beyond in supporting local communities and environmental sustainability.",High_CSR_Reputation
"I appreciate the company's commitment to ethical business practices and fair trade.",High_CSR_Reputation
"Their customer service was top-notch, and they take their corporate responsibility seriously.",High_CSR_Reputation
"There seems to be no evidence of CSR initiatives; however, the product quality is exceptional.",Neutral_CSR_Reputation
"I've never seen a brand put profit over people, which is commendable.",High_CSR_Reputation

In this CSV, the text column contains sentences from different sources describing a brand's reputation and CSR efforts. The label column provides a qualitative assessment categorized as 'High_CSR_Reputation' or 'Neutral_CSR_Reputation'. The 'High_CSR_Reputation' label indicates that the text reflects a positive view of the brand's CSR and reputation, while 'Neutral_CSR_Reputation' suggests a neutral or unclear stance regarding the brand's CSR.

Source of the data:

The dataset was generated using the Infinite Dataset Hub and microsoft/Phi-3-mini-4k-instruct using the query 'brand reputation CSR':

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