A selection of our most recent and relevant publications is listed below. For the full list of GATE publications, please visit the publications page on the main GATE website.
A Framework for Real-Time Semantic Social Media Analysis
This paper presents a framework for collecting and analysing large volume social media content. The real-time analytics framework comprises semantic annotation, Linked Open Data, semantic search, and dynamic result aggregation components. In addition, exploratory search and sense-making are supported through information visualisation interfaces, such as co-occurrence matrices, term clouds, treemaps, and choropleths. There is also an interactive semantic search interface (Prospector), where users can save, refine, and analyse the results of semantic search queries over time.
Quantifying Media Influence and Partisan Attention on Twitter during the UK EU Referendum
User generated media, and their influence on the information individuals are exposed to, have the potential to affect political outcomes. This is increasingly a focus for attention and concern. The British EU membership referendum provided an opportunity for researchers to explore the nature and impact of the new infosphere in a politically charged situation. This work contributes by reviewing websites that were linked in a Brexit Tweet dataset of 13.2 million tweets, by 1.8 million distinct users, collected in the run-up to the referendum. Research materials relating to the work can be found here.
Twits, Twats and Twaddle: Trends in Online Abuse towards UK Politicians
Concerns have reached the mainstream about how social media are affecting political outcomes. One trajectory for this is the exposure of politicians to online abuse. In this paper we use 1.4 million tweets from the months before the 2015 and 2017 UK general elections to explore the abuse directed at politicians. Results show that abuse increased substantially in 2017 compared with 2015. Abusive tweets show a strong relationship with total tweets received, indicating for the most part impersonality, but a second pathway targets less prominent individuals, suggesting different kinds of abuse. Accounts that send abuse are more likely to be throwaway. Economy and immigration were major foci of abusive tweets in 2015, whereas terrorism came to the fore in 2017. The gazetteer of abusive terms used in the work is available here.
Partisanship, Propaganda and Post-Truth Politics: Quantifying Impact in Online Debate
The recent past has highlighted the influential role of social networks and online media in shaping public debate on current affairs and political issues. This paper is focused on studying the role of politically-motivated actors and their strategies for influencing and manipulating public opinion online: partisan media, state-backed propaganda, and post-truth politics. In particular, we present quantitative research on the presence and impact of these three “Ps” in online Twitter debates in two contexts: (i) the run up to the UK EU membership referendum (“Brexit”); and (ii) the information operations of Russia-backed online troll accounts. We first compare the impact of highly partisan versus mainstream media during the Brexit referendum, specifically comparing tweets by half a million “leave” and “remain” supporters. Next, online propaganda strategies are examined, specifically left- and right-wing troll accounts. Lastly, we study the impact of misleading claims made by the political leaders of the leave and remain campaigns. This is then compared to the impact of the Russia-backed partisan media and propaganda accounts during the referendum. In particular, just two of the many misleading claims made by politicians during the referendum were found to be cited in 4.6 times more tweets than the 7,103 tweets related to Russia Today and Sputnik and in 10.2 times more tweets than the 3,200 Brexit-related tweets by the Russian troll accounts. Supplementary materials Twitter elections integrity datasets
What matters most to people around the world? Retrieving Better Life Index priorities on Twitter.
Better Life Index (BLI), the measure of well-being proposed by the OECD, contains many metrics, which enable it to include a detailed overview of the social, economic, and environmental performances of different countries. However, this also increases the difficulty in evaluating the big picture. In order to overcome this, many composite BLI procedures have been proposed, but none of them takes into account societal priorities in the aggregation. One of the reasons for this is that at the moment there is no representative survey about the relative priorities of the BLI topics for each country. Using these priorities could help to design Composite Indices that better reflect the needs of the people. The largest collection of information about society is found in social media such as Twitter. This paper proposes a composite BLI based on the weighted average of the national performances in each dimension of the BLI, using the relative importance that the topics have on Twitter as weights. The idea is that the aggregate of millions of tweets may provide a representation of the priorities (the relative appreciations) among the eleven topics of the BLI, both at a general level and at a country-specific level. By combining topic performances and related Twitter trends, we produce new evidences about the relations between people's priorities and policy makers' activity in the BLI framework.