What do you really want to know?
Getting a feel for it
Content is everywhere. It’s on the Web, on your phone, in your inbox, on your file system. Content is commented, followed, shared, or retweeted. Content is produced through social networks, through Web forms, through mobile applications. Content is created by your customers, your market, by thought leaders, employees, and other enterprises. They are sharing opinions, ideas, comments, requesting information, expressing concerns, discussing technologies and products and influencing. Valuable information is trending within those conversations, threads, and posts. Listen in.
Uncovering and translating social data into tangible insights has become one of the key challenges for Sentiment Analysis technology providers wanting to propose a real social mining solution to their users. Not all opinions are expressed equally and might not have the same business value. Opinions expressed by a market influencer on his/her blog or by a customer through a personal tweet have different impacts. A Sentiment Analysis solution needs to provide a rich set of contextual information that helps you understand what is really being said about you, your products, or your brand and to what extent, and through which channels are impacting you and what you can do about it.
- Brand monitoring: Monitor the sentiment around your brand and products.
- Campaign monitoring: Create and follow the development of a marketing campaign as it unfolds within internal and external content channels.
- Competitive intelligence: Follow your competitors and assess the perception of customers around their activities.
- Identifying influencers: Find out who is talking about your brand across several channels.
Working with the right tools
The OpenText Sentiment Analysis module is a specialized classification engine used to identify and evaluate subjective patterns and expressions of sentiment within textual content. The analysis is performed at the topic, sentence, and document level and is configured to recognize whether portions of text are factual or subjective and, in the latter case, if the opinion expressed within these pieces of content are positive, negative, mixed, or neutral.
Combining machine learning with natural language processing techniques, the OpenText Sentiment Analysis module is one of the most powerful engines available out of the box. With full support of English, French, German, Spanish, and Portuguese, users are able to spot where the subjectivity lies within their content and identify trends on topics, brands, people and more, regardless of the language.
As part of the broader OpenText Content Analytics solution, the Sentiment Analysis module has been designed to handle any type of content from anywhere within your ecosystem. Whether the solution is deployed on-premise, or accessed through the Cloud, users will have access to the same set of features and the same quality of data, available through a single, uniform XML format, making the Sentiment Analysis module the most versatile, enterprise-ready engine available on the market.
Finding emotional intelligence
More often than not, turning content into valuable assets remains the real challenge. We have encapsulated the Sentiment Analysis module within a rich applicative layer, available through a standard REST API, enabling users to leverage the true value of sentiment analysis.
Using OpenText Semantic Navigation, a fully featured semantic search engine, users can access directly a wide range of analytical and visualizations widgets, allowing them to tackle very specific use cases from the moment content processing has begun.
- Create custom queries: Tap into the Content Analytics repository and select topics to create rich queries. Add sources of content; track these queries through time.
- Interactive data visualizations: Use trends and topic maps to navigate through the data; add filters, refine your searches, and get to the heart of what you really want to know.
- Create alerts: Receive notices when a topic of interest pops up in the conversion.
- Get recommendations: Let the engine recommend influencers that you should contact, communities that you should join or issues that you should address.
- Automated extraction of sentiment on topics, sentences and documents.
- Full language support of English, French, Spanish, German and Portuguese.
- Specific configuration for user-generated content out of the box.
- Flexible infrastructure for minimal time-to-business deployment.
- On-premises installation or as a Cloud service.
- Simple XML output.
- Easy customization for specific requirements.
- API library of sentiment-centric and data visualization widgets.