Catherine Somzé, Liu Yang, Tine Schjærff Sørensen, Joe Shaw,Max Grömping, Agata Ludzis-Todorov, Simone Bernardi Pirini
For this research, four sets of tweets were created from the twitter database corresponding to the query drone/drones in the Digital Methods Initiative TCAT archive. The overall query drone/drones was chosen for two reasons. Drones, which are unmanned aerial vehicles (UAV) or Remotely Piloted Aircrafts, have both military and civil uses. They are likely to become the object of public debate and collective fantasy, and they might have been spotted by civilians (their performance may have been witnessed).
The events related to drone appearance were chosen for their different degrees of political relevance and factuality:
1) Drone accident with Australian triathlete (6 April 2014)
2) Drone strike in Pakistan (3 July 2013)
3) Amazon fake/prank (30 November 2013)]
4) Korea - from serious to fun factor (6 May 2014)
From all four data sets, only the data set on the Amazon prank (3) contained a significant amount of geolocated data (known latitude and longitude). A more significant part of the data sets contained mention of the location chosen by Twitter users themselves, but they included both mention of the country and the city. Sometime it also mentioned several cities. For this reason (and the lack of time to go through all four data sets to clean the location to only keep the city mentioned by the user, the choice was made to split four data sets into local (within the country where the events took place) and global locations. This was done by looking at the location column in each data sets and then manually look at all the locations and if it was in the country, to mark it as local.
Several stages of exploratory research were then conducted with the 6 data sets (3 events with corresponding local and global data). This included looking at the distribution of keywords in the user locale (to check accuracy of the sample) and an analysis of the verbatim present in each Tweet - showing a greater degree of description in the local accounts. Also, linked URLs and URL domains were aggregated over time, to show which sources were popular in which audience (global or local). This revealed a few sources of interest that overlapped each region - one was a Pakistani news source, which was cited with some time lag between local and global audiences (in an order that does not suggest time zones as a cause) and one which demonstrated more attention on the initial reports of a North Korean drone strike rather than the later hoax revelations that it was, in fact, a toilet door. However, this later anomaly appears to have been caused by two related spam bots - associated with North and South Korea - of which the North Korean bot did not report the hoax aspect. Global/local accounts containing the Pakistani source were then qualitatively assessed for difference in account.Data extraction
Search terms: australian OR athlete OR triathlon OR Raija OR Ogden OR Geraldton OR Hospital OR Warren OR Abrams OR Simon OR Teakle OR New Era Film
Search terms: Waziristan OR وزیرستان OR Pakistan OR پاکستان OR Miranshah ميرمشاه OR Miran Shah OR Mirali OR Mir Ali OR Mir Ali Tehsil OR Datta Khel OR Dande Darpa OR Darpa Khel Sarai OR Haqqani OR strike
Search terms: Korea OR Cheonggye OR Cheonggyesan OR Gwacheon 한국 OR 과천시 OR 무인 비행기 OR 무인 항공기 OR 청계산
Keywords: amazon AND parrot
Temporal pattern of volume of tweets/retweets
Shows volume of tweets per hour (absolute numbers; red = local and blue = global)
Pakistan event had 2 peaks (first news breaks, second: Al Quaida operatives killed)
Someone from Waziristan told me even it's a thunder storm the children n families run in open field thinking it might b a drone attackIn case of Pakistan global non-URLs appear for egzample Obama name. Sample of tweets: user Mngxitama Bush ordered 50 drones strikes in 8 years. Obama has ordered 375 in four and a half" - pro Adekeye Adebajo. Xolela Mangcu needs education. Conclusions 1) The majority of tweets about any given event are not tweeted from the location 2) Local accounts of events have more specificity 3) Despite (2), the local account of event can be strongly led by the global account.
|png||Australia_global_text.png||manage||52 K||28 Jun 2014 - 19:12||LiuYang|
|jpg||Australia_local_text.jpg||manage||98 K||28 Jun 2014 - 19:14||LiuYang|
|jpg||Korea_global_text.jpg||manage||70 K||28 Jun 2014 - 19:15||LiuYang|
|jpg||Korea_local_text.jpg||manage||104 K||28 Jun 2014 - 19:16||LiuYang|
|jpg||Pakistan_global_text.jpg||manage||62 K||28 Jun 2014 - 19:26||LiuYang|
|jpg||Pakistan_local_text.jpg||manage||76 K||28 Jun 2014 - 19:28||LiuYang|
|jpg||tribune.pk-local-global-01.jpg||manage||3 MB||28 Jun 2014 - 19:41||LiuYang||tribune_URL_flow_Pakistan|