How to Track Twitter on Trendrr
There are many ways to gauge the impact of your message by listening to the Twitterverse and examining microblogging behavior. Microblogging conversation often speaks specifically to the medium, different types of things are conveyed from blog or email communication.
As Twitter moves to being more of a data gathering and sharing network and less of a communication network, being able to aggregate its collective information into intelligence is essential. I wanted to take the time to
illustrate how I am currently using Trendrr to track trend frequency, mind-share, influence, and amplification factors by looking at collective behavior and information on Twitter.
In this post we will look at how you can track social graph statistics as well as how to track words and phase mentions (mind share).
The first important metric is Number of Followers. This helps to frame influence and interaction with one’s network or social graph (i.e. your friends). Examples below:
Social Graph
Number of people that is following you
- Number of people that you are following
.
- Combined view
You can also create a combined view. I like to put them together into a combined view to visualize the follow / following ratio.
Frequency
When your sharing and publishing another good thing to look at is the frequency of your posts. By looking at how often with the follow/following graphs you can get an idea of how your message is being received. If your frequency is high you may see a change one way or another in your follow ratio.
Behavior
-Frequency and volume of posts
Mindshare – Tracking Words & Phrases
Search and Trend
The next thing I like to look at is tracking a specific word or phrase that is of interest for the project I am working on.
By looking at this information you can track the velocity and traction around anything be communicated.
Twitter Search:
Track the number of statuses containing a given keyword or phrase on an hourly and daily basis.
Advanced Trending
Once you have the key metrics you want to collect in effect you can start mashing it up to glean aggregate intelligence and value out of them.
You can cluster views and group things. You can measure against other benchmarks, competition etc. Both in influence and frequency.
I find once you visualize data you can get faster takeaways and better understand whats happening as its happening.
Mashing up Trends for comparative and cluster views.
- Competitive Mashup Views
Annotation
A key part of measuring your results can be showing casual relationships between your efforts and how they impact what your are doing. Annotation of graphs allows for this.
Semantic and Sentiment
- You can use Twitter search operators to further Trend using semantic and other filters.
Here is the list of further refining what you are tracking.
http://search.twitter.com/operators
Search Operators below (from Twitter search)
| Operator | Finds tweets… |
|---|---|
| twitter search | containing both “twitter” and “search”. This is the default operator. |
| “happy hour” | containing the exact phrase “happy hour”. |
| obama OR hillary | containing either “obama” or “hillary” (or both). |
| beer -root | containing “beer” but not “root”. |
| #haiku | containing the hashtag “haiku”. |
| from:alexiskold | sent from person “alexiskold”. |
| to:techcrunch | sent to person “techcrunch”. |
| @mashable | referencing person “mashable”. |
| “happy hour” near:”san francisco” | containing the exact phrase “happy hour” and sent near “san francisco”. |
| near:NYC within:15mi | sent within 15 miles of “NYC”. |
| superhero since:2008-05-01 | containing “superhero” and sent since date “2008-05-01″ (year-month-day). |
| ftw until:2008-05-03 | containing “ftw” and sent up to date “2008-05-03″. |
movie -scary  |
containing “movie”, but not “scary”, and with a positive attitude. |
flight  |
containing “flight” and with a negative attitude. |
| traffic ? | containing “traffic” and asking a question. |
| hilarious filter:links | containing “hilarious” and linking to URLs. |