Hyundai brand has been going through a difficult time recently. A series of failures, breakdowns and problems with high-speed trains connecting Ukrainian cities has triggered a wave of criticism and well-grounded discontent from both passengers, and all other citizens.
In such critical situations negative attitude to a product is sometimes extended to the entire brand. Therefore we wanted to test a hypothesis and check if negative attitude towards Hyundai cars increased due to a rise in popular indignation related to Hyundai Rotem trains.
According to Forbes analysts, one of the key trends in 2013 will be new solutions in the field of visualization and analysis of big data. A Big Data epoch is coming steadily, and now it is not collection, but analysis and visualization of a rising information wave that is coming to forefront. Speed, visualization and functionality are key performance indicators of analytic systems.
Large volumes of information require new visualization techniques, which would show deeper and more detailed interconnections, hierarchy elements, correlations among various objects etc. As noticed by one expert, David McCandless, visualization is one of the forms of data compression. Thus, a good visualization can greatly simplify analysis and processing of Big Data.
We have analyzed a media profile in printed press and online media for seven key Ukrainian parties: Party of Regions, All-Ukrainian Union Fatherland (United Opposition), Ukrainian Democratic Alliance for Reform Vitaliy Klychko, Communist Party of Ukraine, Party Ukraine – Forward!, People's Union "Our Ukraine", All-Ukrainian Union "Freedom". The research period is 1 August – 10 October 2012. The most frequently mentioned one in printed press is the Party of Regions with 2024 publications. The second place is taken by the All-Ukrainian Union Fatherland (United Opposition), which was mentioned in 959 articles. In aggregate, the number of mentions of the opposition parties is 3216.
The leader in online news by the number of mentions with a significant margin is also the Party of Regions with 44,042 articles, with its share of the media presence in the general data (no duplicates) on 7 parties being 45%. The total volume of mentions of the opposition parties including the Communist Party of Ukraine is 55% of the general data or 53,692 publications without duplicates.
All details can be found in our research.
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.
Commenting on various kinds of content on the Web (notes, posts etc.) is an integral part of social media, which emphasizes an interactive nature of online media and enables any participant to express opinion.
In our recent article we’ve already touched upon a topic of monitoring comments in mass media in the internet and their importance. They can sometimes provide much more food for thought and insights than an original article.
Tracking discussions in a variety of media is critical to a complete monitoring and analysis of the information field of the brand. This is complicated however by the fact that comments are reflected in search engines and a majority of monitoring platforms in the form of a general tape of mentions, i.e. in the form of a general incoherent flow of messages where it’s easy to get lost. But in terms of convenience of using the system and tracking people’s reaction to this or that information, it’s much more convenient to see the entire discussion connected with the original article/note.
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.
If you have ever worked in our system, you could notice that a right side of the SemanticForce dashboard had a plethora of filters: geography, author, source etc.
Today we are discussing a geographic filter: how it works, what it can do, and how you can use it.
Geographic identification offered by SemanticForce makes use of different principles for various types of media:
SemanticForce, the online media monitoring platform now tracks Google Plus social network.
Google Plus is a fast-growing social network that was launched on June 28, 2011, and it has acquired more than 20 mln registered users from all over the world just for three weeks. All users have been taking an active part in communicating, sharing ideas, discussing various brands, expressing their opinions…
Within a couple of months Google plans to launch full-fledged business accounts in Google+. But you needn’t wait to start engagement. You can already listen to what other people speak about your brand or you in Google Plus. SemanticForce online media monitoring platform gives you such opportunity.
But you needn’t wait to start engagement. You can already listen to what other people speak about your brand or you in Google Plus. SemanticForce online media monitoring platform gives you such opportunity.