Abstract: An online marketing research measurement that allows a user to derive and/or monitor knowledge metrics, such as awareness metrics, recommendation metrics, advocacy metrics, etc. about a target subject, such as the user's brands and/or products using existing data on the Internet. Rather than requiring responses solicited from active participants in a survey (as in traditional surveys), unsolicited opinion data residing on the Internet can be gathered and processed for deriving various types of knowledge metrics. A recommendation metric can be derived from opinion data gathered from the Internet, which reflects a measure of recommendation opinions about the target subject. Users may identify the specific brand in which they are interested. After an Internet crawler is sent out to select data, the engine cleans the results of poor quality data, codes the data according to the appropriate constructs or variables, and then scores the sentiment using the system's sentiment engine.

Abstract: An online marketing research system where users identify a specific brand and/or competitive brands in which they are interested. An internet crawler engine collects sentiments relating to the identified brands according to a sampling method, which may be created by the user. The results from the internet crawler are refined using a refinement engine. The refined sentiments are then scored by a sentiment engine. Users may view the scored results via a user interface, which itself includes an interactive sentiment modeler. The interactive sentiment modeler provides quantified insights and allows users to select types of charts, the constructs, and timelines that are important to them.

Abstract: An online marketing research measurement that allows a user to derive and/or monitor knowledge metrics, such as awareness metrics, recommendation metrics, advocacy metrics, etc. about a target subject, such as the user's brands and/or products using existing data on the Internet. Rather than requiring responses solicited from active participants in a survey (as in traditional surveys), unsolicited opinion data residing on the Internet can be gathered and processed for deriving various types of knowledge metrics. A recommendation metric can be derived from opinion data gathered from the Internet, which reflects a measure of recommendation opinions about the target subject. Users may identify the specific brand in which they are interested. After an Internet crawler is sent out to select data, the engine cleans the results of poor quality data, codes the data according to the appropriate constructs or variables, and then scores the sentiment using the system's sentiment engine.

Abstract: An online marketing research system is provided that allows users to monitor the sentiment of their brand via existing data on the internet. Users identify the specific brand and competitive brands in which they are interested. After selecting one of the system's sampling methods, or creating a sampling method unique to their needs, the internet crawler is sent out to select according to the plan a specified number of sentiments. The engine cleans the results of poor quality data such as astro-turfing and re-blogging. The sentiments are then scored using the system's sentiment engine, and further cleaned with the hate and profanity engine. The system's crawling engine also gathers data for competitive brands within the same subcategory, category and industry as well as a variety of unrelated brands. Clients use the system's engine interface to visualize the data in an appealing qualitative format.