General Case

This first case is used to examine the Social Media presence of the "Sports Doping" topic, understand the crowd that is engaged with the topic and determine some basic set of words and hashtags that are frequently used in such posts. The query for this case was consisted of plain words, without studying any specific event.

Query Words: doping

Tweets per Month

Contains the count of tweets submitted every month during the researching period.

Sentiment per Month

Contains information about the scores of six basic sentiments (Anger, Disgust, Fear, Joy, Sadness & Surprise), on each month.

Infobox

47.432

47.432 distinct tweets

28.585

28.585 distinct users

48.871

48.871 distinct words

01/12/2016 to 30/05/2017

The time frame of the data is 6 months

Sentiment: Fear

The overall score of our sentiment analysis indicated the main sentiment of the users was Fear.

Most Frequent Words

Contains the most frequent distinct words as extracted from the final data. The table shows the top-10 words along with their frequencies.

# Word Frequency
1 doping 48442
2 anti 8976
3 russia 7132
4 sport 4995
5 twitter 4526
6 ban 3274
7 sharapova 2404
8 athletes 2028
9 olympic 1697
10 news 1461

Most Frequent Hashtags

Contains the most frequent distinct hashtags as extracted from the final data. The table shows the top-10 hashtags along with their frequencies.

# Hashtag Frequency
1 #doping 2339
2 #Doping 593
3 #Russia 500
4 #news 315
5 #Sport 179
6 #WADA 167
7 #039 166
8 #Sharapova 166
9 #cycling 161
10 #sports 160

Most Frequent Users

Contains the most frequent Twitter users as extracted from the final data. The table shows the top-10 users along with their frequencies.

# User Frequency
1 @Tupashe 581
2 @m1ll1onaireman 228
3 @Contrast_Doping 226
4 @Dopinglist 158
5 @ringsau 149
6 @PNS_SportNews 145
7 @DopingReport 124
8 @MeldoniumRussia 124
9 @Rus_Eng_News 121
10 @insidethegames 107

Most Frequent Mentions

Contains the most frequent Twitter mentions as extracted from the final data. The table shows the top-10 mentions along with their frequencies.

# Mention Frequency
1 @wada_ama 220
2 @YouTube 218
3 @MariaSharapova 129
4 @anti_doping 102
5 @c0nvey 68
6 @MichaelPhelps 62
7 @BBCSport 54
8 @iaaforg 53
9 @nytimes 50
10 @ukantidoping 50