8 results found
Fernando S, AmadorDíazLópez J, Şerban O, et al., 2020, Towards a large-scale twitter observatory for political events, Future Generation Computer Systems, Vol: 110, Pages: 976-983, ISSN: 0167-739X
Explosion in usage of social media has made its analysis a relevant topic of interest, and particularly so in the political science area. Within Data Science, no other techniques are more widely accepted and appealing than visualisation. However, with datasets growing in size, visualisation tools also require a paradigm shift to remain useful in big data contexts. This work presents our proposal for a Large-Scale Twitter Observatory that enables researchers to efficiently retrieve, analyse and visualise data from this social network to gain actionable insights and knowledge related with political events. In addition to describing the supporting technologies, we put forward a working pipeline and validate the setup with different examples.
Oehmichen A, Hua K, Diaz Lopez JA, et al., 2019, Not All Lies Are Equal. A Study Into the Engineering of Political Misinformation in the 2016 US Presidential Election, IEEE ACCESS, Vol: 7, Pages: 126305-126314, ISSN: 2169-3536
Molina-Solana M, Kennedy M, Amador Diaz Lopez J, 2018, foo.castr: visualising the future AI workforce, Big Data Analytics, Vol: 3, ISSN: 2058-6345
Organization of companies and their HR departments are becoming hugely affected by recent advancements in computational power and Artificial Intelligence, with this trend likely to dramatically rise in the next few years. This work presents foo.castr, a tool we are developing to visualise, communicate and facilitate the understanding of the impact of these advancements in the future of workforce. It builds upon the idea that particular tasks within job descriptions will be progressively taken by computers, forcing the shaping of human jobs. In its current version, foo.castr presents three different scenarios to help HR departments planning potential changes and disruptions brought by the adoption of Artificial Intelligence.
Piña-Garcia CA, Siqueiros-Garcia JM, Robles-Belmont E, et al., 2017, From Neuroscience to Computer Science: A Topical Approach on Twitter, Journal of Computational Social Science, ISSN: 2432-2717
Amador Diaz Lopez JC, Collignon-Delmar S, Benoit K, et al., 2017, Predicting the Brexit Vote by Tracking and Classifying Public Opinion Using Twitter Data, Statistics, Politics and Policy, Vol: 8, ISSN: 2151-7509
We use 23M Tweets related to the EU referendum in the UK to predict the Brexit vote. In particular, we use user-generated labels known as hashtags to build training sets related to the Leave/Remain campaign. Next, we train SVMs in order to classify Tweets. Finally, we compare our results to Internet and telephone polls. This approach not only allows to reduce the time of hand-coding data to create a training set, but also achieves high level of correlations with Internet polls. Our results suggest that Twitter data may be a suitable substitute for Internet polls and may be a useful complement for telephone polls. We also discuss the reach and limitations of this method.
Lpez JCAD, Pia-Garca CA, 2017, Political participation in Mexico through twitter, Studies in Computational Intelligence, Vol: 693, Pages: 607-618, ISSN: 1860-949X
� Springer International Publishing AG 2017. We used survey data and collected data from the Online Social Network (OSN) Twitter between October the 5th and November the 9th (time window) to provide an overview related to political participation in Mexico. With the survey data we provided a qualitative assessment of political participation in Mexico by examining electoral participation, levels of political participation between regions, Mexicans’ interest in politics and their sources of political information. With our collected data, we described the intensity of political participation in this OSN, we identified locations of high Twitter activity and identified political movements including agencies behind them. With this information, we compare and contrast political participation in Mexico to its counterpart through Twitter. We show that political participation in Mexico seems to be decreasing. However, according to our preliminary results political participation in Mexico through Twitter seems to be increasing. In this regard, our research points towards the emergence of Twitter as a significant platform in terms of political participation in Mexico. Our study analyses the impact of how different agencies related to social movements can enhance political participation trough Twitter. We show that emergent topics related to political participation in Mexico are important because they could help to explore how politics becomes of public interest. The study also offers some important insights for studying the type of political content that users are more likely to tweet.
Amador Diaz Lopez JC, Piña García C, 2017, Political Participation in Mexico Offline and Through Twitter, Online Communities As Agents of Change and Social Movements, Editors: Gordon, Publisher: Information Science Reference, ISBN: 9781522524953
We used survey data and collected data from the online social network Twitter between October 5, 2015 to November 9, 2015 to provide an overview related to political participation in Mexico. With the former we provided a qualitative assessment of participation by examining electoral participation, participation between regions, interest in politics and sources of political information. With Twitter data, we described the intensity of participation, we identified locations of high activity and identified movements including agencies behind them. We compare and contrast participation in Mexico to its counterpart in Twitter. We show that participation seems to be decreasing. However, participation through Twitter seems to be increasing. Our research points towards the emergence of Twitter as a significant platform in terms of political participation in Mexico. Our study analyses the impact of how different agencies related to social movements can enhance participation through Twitter. We show that emergent topics are important because they could help to explore how politics becomes of public interest.
Amador J, Oehmichen A, Molina-Solana M, Characterizing Political Fake News in Twitter by its Meta-Data
This article presents a preliminary approach towards characterizing politicalfake news on Twitter through the analysis of their meta-data. In particular, wefocus on more than 1.5M tweets collected on the day of the election of DonaldTrump as 45th president of the United States of America. We use the meta-dataembedded within those tweets in order to look for differences between tweetscontaining fake news and tweets not containing them. Specifically, we performour analysis only on tweets that went viral, by studying proxies for users'exposure to the tweets, by characterizing accounts spreading fake news, and bylooking at their polarization. We found significant differences on thedistribution of followers, the number of URLs on tweets, and the verificationof the users.
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