Page 1

OVERVIEW

Session #TweetTV at #SXSW Introduction: Great talk by Jenn Deering Davis this morning, people not only tweeted in a very active way but also liked the speech. Amazing statistics: high impact and high reach.

Statistics

Categories

806

338

total tweets

402

340

Retweets

13

Tweets

23

Replies

3

Links

25

Checkins

4.180.513 Impressions Potential impact

1.348.440 Users

users

Pictures

Category

2,4

Text Tweets Pictures Links Replies Checkins

Tweets per user

3.989

Potential reach

Followers per user

Charts

Total tweets

%

Original Tweets

RT

Users

603 120 67 13 3

75 15 8 2 0

340 25 23 13 3

263 95 44 0 0

239 107 60 12 3

Most Active Users charohenriquez

543

num. tweets

34

tweets

958

followers

RAPP

27

160

5912

37

12 16:23 9 mar

tweets

17:09

17:55

18:42

22 19:28

8

9

9

5

20:15

21:01

21:48

22:34

followers

Silis

time

24

tweets

75

num. users

783

followers

22 19

100-150

150-200

200-250

250-300

300-400

400-500

500-750

750-1000

1000-1500

1500-5000 5000-10000

num. followers

>10000

6

26

5

2

5

KerryGorgone

14

tweets

8170

followers

>5

3

9765

followers

13

12

num. tweets per user

4

17

tweets

18 13

50-100

25

23

17

13

0-50

4

33

31 24

vitrue

16

GarnierBBDO

13

tweets

2883

10

followers 27

7

50

1

209 num. users

lisiaf

13

tweets

39

followers

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

1


CATEGORIES Categories Rankings Potential Reach

Number of impressions

Number of users

Number of tweets

Retweets

Text Tweets

Text Tweets

Text Tweets

Text Tweets

Text Tweets

Pictures

Pictures

Pictures

Pictures

Pictures

Links

Links

Links

Links

Links

4

Replies

4

Replies

4

Replies

4

Replies

4

-

5

Checkins

5

Checkins

5

Checkins

5

Checkins

5

-

Charts Impressions per category

Tweets per category

Users per category

Categories Rankings Category Text Tweets Pictures Links Replies Checkins

Total tweets

%

Original Tweets

RT

Users

Impressions

Potential Reach

Tweets/ User

Followers/ User

603 120 67 13 3

75 15 8 2 0

340 25 23 13 3

263 95 44 0 0

239 107 60 12 3

2.592.198 993.003 569.607 22.867 2.838

729.816 800.755 490.145 22.405 2.838

2,5 1,1 1,1 1,1 1,0

3.053 7.483 8.169 1.867 946

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

2


USERS Statistics

338 Number of users

84,5

2,4

12.368

Number of users per category

Number of tweets per user

Number of impressions per user

Top 5 users Most active users

Most popular users

charohenriquez

BillHibbler

34

259.313

tweets

followers

RAPP

27

155.130

310.260

followers

impressions

BillHibbler

130.399

259.313

tweets

followers

impressions

vitrue

4

17

rob_bieber

4

46.896

ASE

256.190

followers

KerryGorgone

5

14

impressions

ThomasMarzano

5

43.334

vitrue

165.996

followers

Most participative users

impressions

Retwitters

mikemost

Most original users

Silis

RAPP

4

24

27

num. categories

num. of RTs

original tweets

ASE

charohenriquez

charohenriquez

3

13

21

num. categories

num. of RTs

original tweets

BillHibbler

lisiaf

vitrue

3

13

17

num. categories

num. of RTs

original tweets

Jas

4

3

BillHibbler

4

8

num. categories

5

jeffarazzi

24

tweets

4

impressions WarrenWhitlock

tweets

tweets

5

1.303.990

WarrenWhitlock

Silis

4

Users with the highest impact

jeffarazzi

KerryGorgone

12

num. of RTs

RAPP

5

3

original tweets

Jas

5

8

num. categories

aks106

num. of RTs

12 original tweets

Charts

108

3989 Followers per user

58

62

HIGH INFLUENCE

54 43

12 1 influence level

Very low 0 to 10 followers

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

Low 10 to 50 followers

Medium-low 50 to 200 followers

Medium 200 to 500 followers

Medium-high High 500 to 1000 1000 to 5000 followers followers

Very high >5000 followers

3


Highlighted tweets Jenn Deering Davis @jdeeringdavis

17:13 - 09 Mar 13

Cat.: Text Tweets

Wow, thank you all for coming to my presentation this morning! It was so much fun. Thanks for your questions! #tweetTV #SXSW

eckfactor Australia @eckfactor

16:34 - 09 Mar 13

Cat.: Text Tweets

Thanks @deeringdavis for your session #tweettv, a fascinating discussion about the impact and influence of twitter on TV #sxsw @planeteck

Gravity Thinking @Gravitythinking

16:14 - 09 Mar 13

Cat.: Text Tweets

79% of people who use social visit Facebook whilst watching tv - huge opps to explore but too closed to analyse #TweetTV #sxsw #SXSWi

Marc Schroeder @marcster70

16:01 - 09 Mar 13

Cat.: Text Tweets

I met a lot of people who say they now people that use Google+ ;-) @jdeeringdavis #tweettv #sxsw

Zoë Ann Baker @zoewithdots

16:01 - 09 Mar 13

Cat.: Text Tweets

Next steps for social tv… to use hash tags more meaningfully and for purpose ie to encourage purchase #TweetTV #RabbitsDoSXSW #sxsw

Erika Digirolamo @ErikaSchmit

15:56 - 09 Mar 13

Cat.: Text Tweets

More shows using real-time tweets to drive people to watch TV live #tweetTV #sxsw

SocialRevoluciónSXSW @RevolucionSXSWi

15:52 - 09 Mar 13

Cat.: Text Tweets

Twitter enables folks to have Parasocial Relationships with the characters on a TV show. Good or Bad? #tweetTV #sxsw #revolucionsxswi

Charo HenriquezScaia @charohenriquez

15:50 - 09 Mar 13

Cat.: Text Tweets

Theory of parasocial relationships. People connect with characters as "friends". Twitter enhances that. #tweettv #sxsw

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

Jim Buckley @JRBuckley68

16:36 - 09 Mar 13

Cat.: Text Tweets

41% of tablet owners & 38% of smartphone owners use devices while watching TV.#sxsw #tweetTV w/ @jdearingdavis via @TiVo - RT @ASE:

Bailey Surrett @ebailey126

16:18 - 09 Mar 13

Cat.: Text Tweets

Twitter is actually encouraging people to watch more programming live. #mullenNC #sxsw #tweettv

RAPP @RAPP

16:13 - 09 Mar 13

Cat.: Text Tweets

Apparently hashtags don't work in commercials in Holland. A really skeptical country. #tweettv #SXSW

Lindsay Sutton @lindsayalk

16:01 - 09 Mar 13

Cat.: Text Tweets

pushing hash tags forward, MY everyday challenge. hash tags 2.0, what does it look like? thoughts? #tweettv #SXSW #effective

Marc Schroeder @marcster70

15:56 - 09 Mar 13

Cat.: Text Tweets

Twitter is a focus group @jdeeringdavis #tweettv #sxsw

Charo HenriquezScaia @charohenriquez

15:52 - 09 Mar 13

Cat.: Text Tweets

Superbowl ads had hashtags this year #tweettv #sxsw

RAPP @RAPP

15:51 - 09 Mar 13

Cat.: Text Tweets

The best ways to engage fans is to tweet with them while they are watching. #tweettv #SXSW

Charo HenriquezScaia @charohenriquez

15:47 - 09 Mar 13

Cat.: Text Tweets

Twitter becomes watercooler. People watch the shows the people they follow "tweet" about. #tweettv #sxsw

4


Jay Deal @Jay_Deal

15:47 - 09 Mar 13

Cat.: Text Tweets

Successful Twitter fan interaction example : Netflix series House of Cards. #tweettv #SXSW #houseofcards

robciampa @robciampa

15:39 - 09 Mar 13

Cat.: Text Tweets

230k tweets / min during peak Super Bowl - wow #tweettv #sxsw

Rinku Sen @ARC_RinkuSen

15:36 - 09 Mar 13

Cat.: Text Tweets

Social media loaded w spoilers by TV watchers. Some shows are made for Twitter: suspense, sports, one time events. #tweettv #SXSW

Christian McDonald @crit

Charo HenriquezScaia @charohenriquez

15:42 - 09 Mar 13

Cat.: Text Tweets

Shows that stream all at once don't fluctuate as much in tweet pattern. #tweettv #sxsw

Andrew Soucy @aks106

15:36 - 09 Mar 13

Cat.: Text Tweets

Apparently the show "Pretty Little Liars" is the most tweeted about show on TV - I have no idea what this show is.... #oldguy #sxsw #tweetTV

Nicole Rose Dion @nicolerosedion

15:34 - 09 Mar 13

Cat.: Text Tweets

That doesn't surprise me - "1 in 3 twitter users has tweeted about TV" #tweettv #sxsw #sxswi @jdeeringdavis

15:31 - 09 Mar 13

Cat.: Text Tweets

Wow, @jddeeringdavis's panel is packed. Glad I came early. #tweettv. Good to see @refreshaustin'r out there. #sxsw

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

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Glossary


Page 1: General Overview: This page shows at a glance the evolution and the global statistics of the session. Statistics − Number of Tweets: Total number of Tweets sent during the session, RTs and replies included. It is shown below, a breakdown of the types of tweets: original tweets (those containing text only) tweets with links, retweets, conversations (tweets as part of a conversation between several users), check-ins and photos. - Number of users: Total number of users who participated in the session using the given hashtag. It also includes users who only sent RTs. - Potential Impact: Number of impressions of the hashtag, which is the number of times that people could have seen the hashtag. This is important because it tells you how many times it has been possible to visualize the hashtag. This number is calculated by multiplying the number of followers of each user by the number of number of Tweets and adding those results. Example: If a user sends 2 tweets and he has 100 followers, the number of impressions generated by the users would be 200. If another user sends 3 tweets and he has 50 followers, the number of impressions generated by this person would be 150 which would make a total of 350 impressions of the session. - Potential Reach: Number of users who have been unable to see the hashtag and could have been impacted by the hashtag. This number is calculated by adding all the followers of each user who participated in the session. Using the previous example, if the session had 2 users, one with 100 followers and the other one with 50, the reach will be 150 followers, regardless of the number of tweets sent. IMPORTANT: both the impact and reach are 'potential' because not everyone may have seen the hashtag and users can have other users in common. - Average number of Tweets per user: this number is the average of Tweets sent per each user. This number is calculated by dividing the number of tweets between the number of users who have participated. RTs included. - Average followers per user: the average number of followers that users of the session have. This figure indicates how influential are the participants in our session. Given that the average number of followers that a Twitter user has is about 250, you can calculate if participants in your session exceed that average. This number is calculated by dividing the sum of followers by the number of users who have participated. - Difference between “Total Tweets” and Tweets: The “Total Tweets” include RTs, links, replies, links and 'Tweets'. 'Tweets' are the ones containing only text. ChaRTs There are different types of graphs in the report Tweet Category: − Temporal Evolution: shows the time evolution of the tweets sent by users. Tweet Category takes the first and last tweet and draws the timeline of the session. Thanks to this chart you will be able to identify the moment people tweeted the most or the least. − Influence of Users: shows the influence of the users who participated in the session. On the vertical axis you will find the total number of users and on the horizontal one, the number of followers of those users. As we move to the right part of the graph you will see the users who have a greater number of followers and therefore influence. The higher the columns on the right, the higher influence of your users. − User activity: shows the number of tweets sent by users. The vertical axis shows the number of tweets sent and the horizontal one the number of users who have participated. Page 2: Statistics of the categories: on this page you will find the detailed statistics for each category.

Rankings of categories: This ranking shows which categories have reached the top 5 according to several statistics. It is interesting to note that although a category may have a greater number of tweets that another one, it could have a minor number of impressions (lower impact). The rankings show the categories with the highest reach, impact, number of users, number of tweets and number of RTs.

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

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ChaRTs: − Impact by category: This graph shows which category has the highest number of impressions and therefore the highest impact. − Tweets by category Chart: This chart shows which category has the highest number of total tweets. − Users by category Chart: This chart shows which category has the highest number of users. Table of categories: This table shows detailed statistics for each category; these statistics are the same variables as the global statistics of the session but applied to each of the category. Thus you can see which category gets more impact, more users, and so on. It is worth taking a second to consider this table as very interesting conclusions can be obtained from it. Page 3: User Rankings Tweet Category offers different kinds of user rankings: − Most active users: the ones who tweeted the most using the hashtag. RTs included. − Most popular users: the ones who have the highest number of followers in the session. − Users with the highest impact: the ones who generated the highest number of impressions. − Most participative users: the ones who participated in more categories. − Most retweeter users: the ones who sent the highest number of RTs. − Most original users: the ones who sent the highest number of original tweets (No RTs).

Analysis of the session '#TweetTV at #SXSW' created with Tweet Category

8

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Social TV in SXSW

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