SENTIMENT CASCADES IN THE 15M MOVEMENT Sentiment cascades in the 15M movement

Abstract Recent grassroots movements have suggested that online social networks might play a key role in their organization, as adherents have a fast, many-to-many, communication channel to help coordinate their mobilization. The structure and dynamics of the networks constructed from the digital traces of protesters have been analyzed to some extent recently. However, less effort has been devoted to the analysis of the semantic content of messages exchanged during the protest. Using the data obtained from a microblogging service during the brewing and active phases of the 15M movement in Spain, we perform the first large scale test of theories on collective emotions and social interaction in collective actions. Our findings show that activity and information cascades in the movement are larger in the presence of negative collective emotions and when users express themselves in terms related to social content. At the level of individual participants, our results show that their social integration in the movement, as measured through social network metrics, increases with their level of engagement and of expression of negativity. Our findings show that non-rational factors play a role in the formation and activity of social movements through online media, having important consequences for viral spreading

Sentiment cascades in the 15M movement

Recent grassroots movements have suggested that online social networks might play a key role in their organization, as adherents have a fast, many-to-many, communication channel to help coordinate their mobilization. The structure and dynamics of the networks constructed from the digital traces of protesters have been analyzed to some extent recently. However, less effort has been devoted to the analysis of the semantic content of messages exchanged during the protest. Using the data obtained from a microblogging service during the brewing and active phases of the 15M movement in Spain, we perform the first large scale test of theories on collective emotions and social interaction in collective actions. Our findings show that activity and information cascades in the movement are larger in the presence of negative collective emotions and when users express themselves in terms related to social content. At the level of individual participants, our results show that their social integration in the movement, as measured through social network metrics, increases with their level of engagement and of expression of negativity. Our findings show that non-rational factors play a role in the formation and activity of social movements through online media, having important consequences for viral spreading.Comment: EPJ Data Science vol 4 (2015) (forthcoming

Quantifying echo chamber effects in information spreading over political communication networks

Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects of echo chambers in information spreading phenomena over political communication networks. Mining 12 million Twitter messages, we reconstruct a network in which users interchange opinions related to the impeachment of the former Brazilian President Dilma Rousseff. We define a continuous {political position} parameter, independent of the network's structure, that allows to quantify the presence of echo chambers in the strongly connected component of the network, reflected in two well-separated communities of similar sizes with opposite views of the impeachment process. By means of simple spreading models, we show that the capability of users in propagating the content they produce, measured by the associated spreadability, strongly depends on their attitude. Users expressing pro-impeachment sentiments are capable to transmit information, on average, to a larger audience than users expressing anti-impeachment sentiments. Furthermore, the users' spreadability is correlated to the diversity, in terms of political position, of the audience reached. Our method can be exploited to identify the presence of echo chambers and their effects across different contexts and shed light upon the mechanisms allowing to break echo chambers.Comment: 9 pages, 4 figures. Supplementary Information available as ancillary fil

Emotions, Demographics and Sociability in Twitter Interactions

The social connections people form online affect the quality of information they receive and their online experience. Although a host of socioeconomic and cognitive factors were implicated in the formation of offline social ties, few of them have been empirically validated, particularly in an online setting. In this study, we analyze a large corpus of geo-referenced messages, or tweets, posted by social media users from a major US metropolitan area. We linked these tweets to US Census data through their locations. This allowed us to measure emotions expressed in the tweets posted from an area, the structure of social connections, and also use that area's socioeconomic characteristics in analysis. %We extracted the structure of online social interactions from the people mentioned in tweets from that area. We find that at an aggregate level, places where social media users engage more deeply with less diverse social contacts are those where they express more negative emotions, like sadness and anger. Demographics also has an impact: these places have residents with lower household income and education levels. Conversely, places where people engage less frequently but with diverse contacts have happier, more positive messages posted from them and also have better educated, younger, more affluent residents. Results suggest that cognitive factors and offline characteristics affect the quality of online interactions. Our work highlights the value of linking social media data to traditional data sources, such as US Census, to drive novel analysis of online behavior.Comment: International Conference on the Web and Social Media (ICWSM2016

From continuous to discontinuous transitions in social diffusion

Models of social diffusion reflect processes of how new products, ideas or behaviors are adopted in a population. These models typically lead to a continuous or a discontinuous phase transition of the number of adopters as a function of a control parameter. We explore a simple model of social adoption where the agents can be in two states, either adopters or non-adopters, and can switch between these two states interacting with other agents through a network. The probability of an agent to switch from non-adopter to adopter depends on the number of adopters in her network neighborhood, the adoption threshold $T$ and the adoption coefficient $a$, two parameters defining a Hill function. In contrast, the transition from adopter to non-adopter is spontaneous at a certain rate $\mu$. In a mean-field approach, we derive the governing ordinary differential equations and show that the nature of the transition between the global non-adoption and global adoption regimes depends mostly on the balance between the probability to adopt with one and two adopters. The transition changes from continuous, via a transcritical bifurcation, to discontinuous, via a combination of a saddle-node and a transcritical bifurcation, through a supercritical pitchfork bifurcation. We characterize the full parameter space. Finally, we compare our analytical results with Montecarlo simulations on annealed and quenched degree regular networks, showing a better agreement for the annealed case. Our results show how a simple model is able to capture two seemingly very different types of transitions, i.e., continuous and discontinuous and thus unifies underlying dynamics for different systems. Furthermore the form of the adoption probability used here is based on empirical measurements.Comment: 7 pages, 3 figure

Political conversations on Twitter in a disruptive scenario: The role of "party evangelists" during the 2015 Spanish general elections

"This is an Accepted Manuscript of an article published by Taylor & Francis in The Communication Review on 2019, available online: https://www.tandfonline.com/doi/full/10.1080/10714421.2019.1599642"[EN] During election campaigns, candidates, parties, and media share their relevance on Twitter with a group of especially active users, aligned with a particular party. This paper introduces the profile of ¿party evangelists,¿ and explores the activity and effects these users had on the general political conversation during the 2015 Spanish general election. On that occasion, the electoral expectations were uncertain for the two major parties (PP and PSOE) because of the rise of two emerging parties that were disrupting the political status quo (Podemos and Ciudadanos). This was an ideal situation to assess the differences between the evangelists of established and emerging parties. The paper evaluates two aspects of the political conversation based on a corpus of 8.9 million tweets: the retweet- ing effectiveness, and the sentiment analysis of the overall conver- sation. We found that one of the emerging party¿s evangelists dominated message dissemination to a much greater extent.The present research was supported by the Ministerio de Economia y Competitividad [CSO2013-43960-R] [CSO2016-77331-C2-1-R]. The present research was supported by the Ministerio de Economia y Competitividad, Spain, under Grants CSO2013-43960-R ("2015-2016 Spanish political parties' online campaign strategies") and CSO2016-77331-C2-1-R ("Strategies, agendas and discourse in electoral cybercampaigns: media and citizens"). This work was possible thanks to help received from Emilio Giner in his task of extracting the corpus of tweets and from assistance provided by Mike Thelwall and David Vilares in the use of the SentiStrength application. We have benefited from valuable comments on drafts of this article from professors Joaquín Aldás, Amparo Baviera-Puig, Guillermo López-García, and especially Lidia Valera-Ordaz.Baviera, T.; Sampietro, A.; García-Ull, FJ. (2019). Political conversations on Twitter in a disruptive scenario: The role of "party evangelists" during the 2015 Spanish general elections. The Communication Review. 22(2):117-138. https://doi.org/10.1080/10714421.2019.1599642S117138222Alvarez, R., Garcia, D., Moreno, Y., & Schweitzer, F. (2015). Sentiment cascades in the 15M movement. EPJ Data Science, 4(1). doi:10.1140/epjds/s13688-015-0042-4Anduiza, E., Cristancho, C., & Sabucedo, J. M. (2013). Mobilization through online social networks: the political protest of theindignadosin Spain. Information, Communication & Society, 17(6), 750-764. doi:10.1080/1369118x.2013.808360Anstead, N., & O’Loughlin, B. (2011). The Emerging Viewertariat and BBC Question Time. 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Finding polarised communities and tracking information diffusion on Twitter: The Irish Abortion Referendum

The analysis of social networks enables the understanding of social interactions, polarisation of ideas, and the spread of information and therefore plays an important role in society. We use Twitter data - as it is a popular venue for the expression of opinion and dissemination of information - to identify opposing sides of a debate and, importantly, to observe how information spreads between these groups in our current polarised climate. To achieve this, we collected over 688,000 Tweets from the Irish Abortion Referendum of 2018 to build a conversation network from users mentions with sentiment-based homophily. From this network, community detection methods allow us to isolate yes- or no-aligned supporters with high accuracy (90.9%). We supplement this by tracking how information cascades spread via over 31,000 retweet-cascades. We found that very little information spread between polarised communities. This provides a valuable methodology for extracting and studying information diffusion on large networks by isolating ideologically polarised groups and exploring the propagation of information within and between these groups.Comment: 44 pages, 4 appendices, 18 figure