Social MediaNetwork AnalysisFocus : Twitter

Social Network Analysis?

Social Network Analysis is a range of techniques, methods and visualisation of connections between people and network content.

We implement this methodology in an innovative way, and fully integrated with our BrandCare software.

In the Twitter Social Network Analysis feature, everything which is monitored, tagged or classified within the platform can generate network visualisations.

Twitter Social Network AnalysisEverything that is monitored in Twitter can be transformed into a network

Each point represents a Profile and each line represents a Connection

Twitter Social Network Analysis

É possível analisar Influenciadores,

Ativadores, Clusters, Fluxos de

Informação e outros elementos da

estrutura da rede em detalhes.

Information about each profile can be seen in details with a click.

With our tool, you can:• Zoom into the network, • Fliter by different Metrics,

Tags and Groups, • Find and analyse specific

Clusters and export as an Image

The 5 main applications of Social Network Analysis:

. Find and analyse influencers

. Find and analyse activators

. Analyse Information Flow

. Measure Campaign Impact

. Analyse Clusters and Communities

1. Find Influencers

Network metrics take Influence Measurement one step further.

Providing a deeper understanding than just the volume of mentions or dissemination potential, metrics such as In Degree measure the real impact of people, profiles and channels to measure influence and authority.

Influencer

In the Twitter Social Network Analysis module, the generated visualisation will already display profiles with the highest In Degree. By opening the ‘Filter’ box it is possible to change the view to analyse different items.

1. Find Influencers

2. Find Activators

Measurement of Engagement can be improved with Network Metrics.

With BrandCare, it is possible to also analyse who transforms engagement in activation of other people.

Out Degree metrics (OutDegree), in combination with other metrics such as tag classification, sentiment etc. allows the user to find other profiles showing engagement by talking and sending information to others.

By using the Out Degree filter in the Twitter Social Network Analysis, it is possible to find out which profiles activated and interacted with others the most through Mentions and Retweets.

2. Find Activators

3. Analyse Information Flow

Where did the information pass through to reach more people?

Analysing the Information Flow allows the generation of more insights connected to Content Viralization and even Crisis Outbreak.

In the example to the left, the information travelled through several steps via ‘Retweets’, reaching a lot more people than the initial source had between his/her followers.

In the example to the right, we have the typical broadcast structure with a news portal as the hub.

3. Analyse Information Flow

4. Analyse Campaign Impact

Sponsored campaigns with bloggers, influencers, ads and media channels can have the impact in the network measured in Twitter.

Twitter serves as a hub of message circulation, links and hashtags, which we can analyse in relation to specific advertisement campaigns.

The map above is normally used for brands that run Youtube campaigns. In thiscase Youtube becomes the hub between people that are sharing the video.

5. Analyse Clusters and Communities

Clusters are groups of people who are more connected to eachother, than to the rest of the network as a whole.

These connections could mean that they are talking about the same theme, possess the same demographic characteristic, follow the same types of references and/or have another type of similarity.

Within Twitter, it can even mean that it is a community with repeated contacts.

5. Analyse Clusters and Communities

BrandCare is able to source clusters present in the network, via analysis of network algorithms. It is possible to see each one of them in an isolated form, filter data of each group and even generate a wordcloud of profile details and tweets of each cluster.

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