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This is a short review of extra capabilities of search queries on Semantic Force platform, which will show you some other ways of tailoring and detailing sought-after selections. If you like, you can set such search in our system yourself (we give specific examples below) or ask us to make extra settings required.

1. Search in headlines.
The search in headlines allows searching objects only in headlines, rather than in the entire text.
How to use. Using this query you can quickly learn how often your brand is mentioned in headlines of articles. Moreover, you can see, how widely a certain article has spread in the online space, if you know its exact title; or how well a piece of news has played its role, with one or more key words presumed in the headline.
How to set. Create a topic, set main objects of the query (e.g. HTC). Then press “Show Advanced Search” and create a query, e.g. title:"One" Thereby you will find all mentions, where headlines contain a name of a new product line of HTC One smartphones. They will be headlines of articles for online mass media and blogs, and message content etc. for microblogs.

2. Search with distance. It is sometimes not enough to indicate the context of search queries just in words; at times it is also required to specify proximity of explicative words. For such cases one can use a search with indicated distance from one word to the other (the distance is measured by the number of words between them).
How to use. This search query can help in numerous situations. For instance, it helps search mentions of certain types of goods or their features – in those cases context words should be located in the text not far from your brand, and you will see the most relevant feedbacks in search results. The search with distance is useful for such queries as “wanna buy a phone”: there can be usually a few words between “buy” and “phone”: I’ve long wanted to buy a new phone, I planned to buy my wife in the Internet a phone etc. To trace all those queries, it’s worth using the above option.
How to set. Create a topic, set main objects of the query (e.g. Messi in the context of “god”). Then press “Show Advanced Search” and create a query: “Messi god”~4. You will see all mentions, where Messi is compared to god, and are likely to avoid tropes like “football god was in favour of the team” and other mentions of god, which are not related to the person of Lionel Messi. The higher is the number after tilde, the farther are the words from each other.

There is hardly a person who would be surprised at online mass media monitoring; the first such systems emerged as early as in the distant 20th century. However the web has been developing at a terrific speed, and now online monitoring services allow meeting a wider range of challenges. One challenge is to monitor comments to articles.


While commentators value more their reputation, say, on forums, in blog services or in social webs knowing about a possible ban or trasuring their relations with online friends, users are more emotional, categorical and frank to comment on articles hiding behind a nickname.

The analysis of comments is a rich source of insights. Apart from commentators’ frankness, important factors also include an occasionally large size of the “focus group” and a “brainstorm” effect.