Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The use of location based data analysing tools is an important part of geomarketing strategies among entrepreneurs. One of the key elements of interest is social media data shared by the users. This data is analysed both for its content and its location information, the results help to identify trends represented in the researched regions. In order to verify the possibilities of analysing and processing of geotagged social media data, application programming interfaces (APIs) of social networks were examined for their ability to generate reports from the collected data. The first results of using the system have indicated the possibility of collecting and analysing information generated by Twitter users in real time. Trends and geographical distribution in time can be observed. Further research showed that comparing results and further processing was possible.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
250--260
Opis fizyczny
Bibliogr. 14 poz., rys., wykr.
Twórcy
autor
- Department of Applied Informatics, Faculty of Management and Economics, Gdańsk University of Technology
Bibliografia
- [1] Boyd, D. (2007). Why youth (heart) social network sites: The role of networked publics in teenage social life. … Series on Digital learning–Youth, Identity, and Digital …, 7641. doi:10.1162/dmal.9780262524834.119
- [2] floatingsheep: Premier League teams on Twitter (or why Liverpool wins the league and the Queen might support West Ham). (2013). Retrieved April 21, 2014, from http://www.floatingsheep.org/2013/01/premier-league-teams-on-twitter-or-why.html
- [3] Hecht, B., & Stephens, M. (2014). A Tale of Cities : Urban Biases in Volunteered Geographic Information. Retrieved from http://www.users.cs.umn.edu/~bhecht/publications/bhecht_icwsm2014_ruralurban.pdf
- [4] How Smartphones are Changing Consumers’ Daily Routines Around the Globe. (2014). Retrieved September 01, 2014, from http://www.nielsen.com/us/en/insights/news/2014/how-smartphones-are-changingconsumers-daily-routines-around-the-globe.html
- [5] Meeker, M. (2014). Internet trends 2014-code conference. Retrieved May. Retrieved from http://www.kpcb.com/internet-trends
- [6] Mitchell, S., & Harris, P. (2013). System and Method for aggregating and distributing geotegged content. United States.
- [7] Morstatter, F., Lubold, N., & Pon-Barry, H. (2014). Finding Eyewitness Tweets During Crises. arXiv Preprint arXiv: …. Retrieved from http://arxiv.org/abs/1403.1773
- [8] Morstatter, F., Pfeffer, J., Liu, H., & Carley, K. (2013). Is the Sample Good Enough? Comparing Data from Twitter’s Streaming API with Twitter's Firehose. ICWSM. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM13/paper/viewPDFInterstitial/60 71/6379
- [9] Riegner, C. (2007). Word of Mouth on the Web: The Impact of Web 2.0 on Consumer Purchase Decisions. Journal of Advertising Research, 47(4), 436. doi:10.2501/S0021849907070456
- [10] Rost, M., Cramer, H., Belloni, N., & Holmquist, L. (2010). Geolocation in the mobile web browser. Proceedings of the 12th …, 423. doi:10.1145/1864431.1864468
- [11] Stephens, M., & Poorthuis, A. (2014). Connecting the social and the spatial networks on Twitter. Computers , Environment and Urban Systems Follow Thy Neighbor.
- [12] Twitter- About the company. (2014). Retrieved November 24, 2014, from https://about.twitter.com/company
- [13] WHERE. (2014). Retrieved November 24, 2014, from http://whereproject.com/
- [14] Zook, M., & Poorthuis, A. (2014). Offline Brews and Online Views: Exploring the Geography of Beer Tweets. In The Geography of Beer (pp. 201–209). Springer Netherlands. doi:10.1007/978-94-007-7787-3_17
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f7350245-adce-4a38-ac13-55e855c4379a