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Published on June 26th, 2014 | by EJC


Featured Tool: Tame

In a nutshell:

Tame analyses Twitter-user timelines and gives a real-time overview of the most relevant links, topics and accounts found amongst them. Recognising the unique potential of Twitter’s function as a newsgathering tool, with hundreds and thousands of users producing new Tweets every few seconds, Tame is the first tool released by tazaldoo, a Berlin-based startup founded in 2012. The objective of the startup is to “fight the information overload on the real-time web”,  according to Co-founder Torsten Müller. It debuted on the U.S. market in 2013 via the German Silicon Valley Accelerator Programme and is now considered one of the most recent data mining tools with big potential.


The Tame algorithm provides users with an analysis of their own Twitter timeline and a global view of the same search. The results are displayed in three Top-10 lists entailing, respectively, the most popular links, hashtags and mentions. The analysis is delivered via e-mail in real-time in daily or weekly digests at pre-requested times, and can be shared with Twitter followers or via a short link.

The German publication taz labels Tame as an up-to-the-minute version of Google News, with some additional perks that render it a high-potential, unique Twitter search tool. For example, those actively generating and using Tweet lists may apply the analysis to each specific list. The Tweet Editor lets users choose from Tame-suggested hashtags to produce the most up-to-date tweets and become a relevant part of the discussion. Additionally, Tame Widgets can be implemented into a website, indicating the most important content, topics and users on a specific topic (for journalists) or a brand (for businesses).

In the Follower Analysis feature, Tame allows for the analysis of an account’s followers, thus enabling optimal communication and the identification of leading opinions, although this is most beneficial for business users. Something else that Tame brings to the table is an option for those users who would like to contribute, for example by creating and suggesting their own solutions, customising licenses and conducting own long-term analyses.


Through its own algorithm, Tame focusses on the quality and number of sources, which they state is often more important than the mere number of retweets. This means that, for example, links used by influential users have greater weight in the final ranking (WSJ). The algorithm analyses Tweets according to classifiers such as hashtags, mentions, links, images, videos or text. The relevance ranking is generated by weighing the numbers of individual sources that use a specific link, hashtag or mention. Similarly, in the Follower Analysis, Tame indexes the follower accounts of a specific user and analyses them according to a subset of their respective influence or location.


Tame draws content from either one Twitter timeline or all timelines globally for any time period between 24 hours and 7 days. Users may narrow search results down via a Time Slider and these are then loaded anew. Multimedia are filtered according to imagery and videos. Plus, users may connect a total of three Twitter accounts for analysis and analyse content in over 20 different languages.

Logically, within one’s own timeline and lists, the quality of results depends on the composition of a Twitter user’s network, that is, any timeline or list they ask Tame to analyse. In contrast, when Tame searches and analyses Twitter globally, the amount of data is most important to receive to most relevant results.

Case studies

  1. European Elections Debate 2014: Within roughly one and a half hours, the analysis produced this overview of the debate, revealing in real-time the most popular links (,, hashtags (#telleurope, #ep2014) and mentions (Martin Schulz, Guy Verhofstadt).
  2. International Journalism Festival 2014: Of over 40,000 total Tweets, close to 9,000 included the representative hashtag #ijf14, while topics related to @datajournalism and accounts such as @journalismfest were among the most popular ones (here).
  3. Analysing the accounts of political parties in Germany disclosed their communication behavior with their followers. The time period under scrutiny revealed that two of the smaller parties, the Alternative for Germany and the Pirates, most closely and effectively communicated with their own followers. Bigger parties such as the Christian Conservatives or Social Democrats were included in their followers’ tweets only to a limited extent. The analysis also determined which topics were most popular among each party’s followers, for example hashtags related to the NSA spying affair and Edward Snowden were used most by Pirates-followers.

Photo: Snapshot of the final results after analysing Twitter content, topics and users during the International Journalism Festival 2014.

What’s in it for journalists?

  • Staying on top of discussions and receiving news as it breaks. Subscribing to hundreds and thousands of accounts is not uncommon for Twitter users in the field of professional journalism – being able to sift through yet unspecified masses of tweets is thus inevitable.
  • Real-time delivery of developing stories in foreign settings. When reporting on a particular topic in another country or time zone, Tame analyses in real-time, for example expert opinions, without the reporter having to search his or her Timeline manually.
  • Political crises. When a politically charged crisis environment is on the brink of collapse and sources may or may not be trustworthy, it is important to know which hashtags are relevant, which have already lost referral to the general discussion, and who wields an influential opinion. Journalists can quickly find the most up-to-date hashtag by simply adjusting the Time Slider and refreshing the ranking, thus participating in the most relevant discussion.

About the Author:

Pauline Lendrich currently writes and works for the European Journalism Centre. She is originally from Germany and studied International Relations and Security at Maastricht University as well as at the University of Maryland, Baltimore County. Follow on Twitter: @Paulinelliott


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