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Semantic contextualization-social-media-white-paper
 

Semantic contextualization-social-media-white-paper

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    Semantic contextualization-social-media-white-paper Semantic contextualization-social-media-white-paper Document Transcript

    • Semeon Analytics and Semantic Contextualization Semeon White Paper by Alkis Papadopoullos, CTO January 2012 © Semeon 2012
    • The mechanics of the semantic contextualizationto determine the best actionAs Social Media Monitoring comes of age, and users of existingplatforms become more aware of how various products work toassist with monitoring, the ability to go beyond brand monitoringand frequency based determination of potentially relevant tags isbecoming more important. Knowing the distribution of mentionsof a keyword, brand or concept per key sites and networks is nowconsidered a given, but putting that keyword, brand or concept incontext is an effective way to understand whether the mentionsare actually relevant, and therefore a surer way to determine ifcall to action, and/or engagement are necessary and whetherthey will have the desired effect. To address this need, we presentsome ideas around the mechanics of semantic contextualization.Above and beyond habitual customer expectations with socialmedia platforms, most users of these platforms have a set of verytangible expectations such as obtaining a synthesis or summaryof a given problem, obtaining a recommendation or call to actionto address a particular issue, effectively reducing the time it takesto try and achieve these goals, etc. However, this proves verydifficult to accomplish if analysis is based solely on usual socialmedia monitoring metrics such as number of mentions, share ofvoice or brand reach, as none of these provide any context.Semantic analysis can help to achieve these goals, primarilybecause it involves associating to each word from user comments,the meaning of the word; it is thus equivalent to extracting andstoring concepts rather than keywords. By identifyingconcepts, synonyms, named entities (people, places, brand names,etc.) it is possible to achieve three important goals that are thecornerstones of identifying meaning and intent, namely:  Avoid breaking up conceptual units consisting of multiple words (“information management system”)  Use different semantic categories to facilitate discovery of unexpected related themes or concepts  Establish correlations between concepts in order to provide context for analysis 2 | Page
    • As an example it does not suffice to know that a particular concept is being commented on in a negative way, but rather it is necessary to understand what specifically is perceived as negative. Knowing that users complain about the notion of “traffic information” when reviewing GPS systems could be somewhat useful, while understanding that they are specifically frustrated with the inability of “lane assist” features to help navigate traffic is far more useful to those developing GPS systems. An immediate action to focus product enhancement along the lines suggested by consumer feedback emerges more rapidly. This is but one possible use among many. By combining this Semeon Analytics combines semantic analysisapproach with robust and results in context sentence level Semeon Analytics helps to achieve precisely such goals. Using asentiment analysis, it natural language processing approach that combines semanticis possible to overlay analysis with proprietary machine learning algorithms we strive sentiment atop the to help users reliably identify meaning in online content and context provided by more importantly to provide analysis that affords them views and reports of results in context. This enhances customers’ ability to our system. reliably mine data for actionable information and does so all the while reducing the time that must be spent analyzing data in order to draw reliable conclusions. By combining this approach with robust sentence level sentiment analysis, it is possible to overlay sentiment atop the context provided by our system. This in turn means that we can identify whether a concept evoked in a comment is positive or negative but then go significantly further, by identifying which specific aspects of a given concept are also positive or negative. To do so Semeon has developed proprietary sentiment analysis algorithms that are updated on a regular basis in order to continue to increase their accuracy. Please look into our sentiment analysis white paper for more details. 3 | Page
    • Another very significant advantage of semantic contextualization is the ability to compute a poster’s semantic profile based on analysis of their various posts and comments. Semeon’s Social platform can thus avoid falling into the trap of determining influencers based solely on the frequency of posts, a method common to many social media monitoring platforms, and rife with problems among which is the direct exposure to spammers who rely on frequency of posts to get a message across. By mapping the most relevant concepts evoked by a poster, we can determine several very interesting things:  How rich (i.e. how diverse in subject matter) is their contribution to the conversation about a topic  How much conceptual overlap there is with other posters  Who are the promoters of the most relevant concepts …go significantly being evoked by postersfurther, by identifying  Whether there are trends over time relating to certain concepts and which posters are behind those trendswhich specific aspects  Combining this with other factors such as retweets inof a given concept are order to generate a more complete influence map also positive or  Understand far better on what specific subjects to engage on with internet posters negative. In summary, Semeon Analytics’ semantic contextualization allows customers to more rapidly gain actionable insight into important topics or themes of interest to them, understand the specifics about why a given concept is negative or positive, and derive far more useful views of who are the real influencers impacting conversations, opinions, buying decisions, etc. Please feel to contact us at info@semeon.com if you interested in further information or a demo of our product. FOR MORE INFORMATION Semeon Analytics 4 | Page