Marc Esteve Del Valle

Social Media in Educational Practice: Faculty Present and Future Use of Social Media in Teaching

This paper presents results from a questionnaire (n=333) designed to gain an understanding of instructor motivations and experience with social media use in educational practice. Data on overall use of social media, and instructors’ use of social media in classes are applied to assess factors leading to present and future use of social media in teaching, using a framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. Our findings show use in teaching is driven by factors associated with UTAUT’s Performance Expectancy construct, i.e., personal engagement with social media, and Moderating Condition of age, with older participants making greater use of social media in teaching. Other constructs associated with use are Habit (experience teaching online), Social Influence (colleagues using social media), Effort Expectancy (awareness of barriers, staying informed), Facilitating Conditions (institutional technology support) and Moderating Conditions (teaching at a two-year college).

Opinion leadership in parliamentary Twitter networks: A matter of layers of interaction?

This article seeks to test whether Twitter is contributing to the appearance of new opinion leaders or empowering already visible political leaders. The study is based on a data set spanning from January 1, 2013 to March 31, 2014 that covers all relationships (4,516), retweets (6,045) and mentions (19,507) of Catalan parliamentarians. The data sustains that having a parliamentarian position increases the probability of being an opinion leader of the following–follower and mention networks, but not so much of the retweet network. Although Twitter parliamentary networks reproduce leaderships “as usual,” the most central opinion leaders in the retweet network are not official party leaders. Twitter activity, not official leadership, is a stronger predictor of centrality for both retweets and mentions received.ABSTRACT This article seeks to test whether Twitter is contributing to the appearance of new opinion leaders or empowering already visible political leaders. The study is based on a data set spanning from January 1, 2013 to March 31, 2014 that covers all relationships (4,516), retweets (6,045) and mentions (19,507) of Catalan parliamentarians. The data sustains that having a parliamentarian position increases the probability of being an opinion leader of the following–follower and mention networks, but not so much of the retweet network. Although Twitter parliamentary networks reproduce leaderships “as usual,” the most central opinion leaders in the retweet network are not official party leaders. Twitter activity, not official leadership, is a stronger predictor of centrality for both retweets and mentions received.

Organization Still Matters: Parties' Characteristics, Posting and Followers' Reactions on Facebook

Use of social media by political parties has become a part of their communication strategies. In Catalonia, where around 20% of Internet users obtain political information through Facebook and Twitter, parties use these channels widely. This article has examined 814 posts, 5,772 comments, 52,470 likes and 25,907 shares from the official Facebook pages of Catalan parties in order to ascertain the relevance of the classical party characteristics party size, level of institutionalization, centralization of decision-making, position at the ideological cleavages on how parties and their followers behave on Facebook. The data sustain that the characteristics of Catalan parties have an influence on their posting behaviour on Facebook, and mould the reactions comments, likes and shares of their Facebook followers to these posts. The results further show that small and new parties achieve greater engagement than bigger and more institutionalized parties.

Determining the Function of Political Tweets

We study the discursive practices of politicians and journalists on social media. For this we need more annotated data than we currently have but the annotation process is time-consuming and costly. In this paper we examine machine learning methods for automatically annotating unseen tweetsbased on a small set of manually annotated tweets. Forimproving the performance of the learner, we focus onmethods related to training data expansion, like artificialtraining data, active learning and incorporating languagemodels developed from unannotated text.

Unpredictably Trump?: Predicting Clicktivist-like Actions on Trump's Facebook Posts During the 2016 U.S. Primary Election

This study aims to identify the factors that might cause a Facebook post to be liked by Facebook users. We analyze all the Facebook posts made by Donald Trumps campaign during the U.S. 2016 primary election. Several possible variables were considered, such as the types of Facebook posts, the use of pronouns and emotions, the inclusion of slogans and hashtags, references made to opponents, as well as candidate mentions on national television. The results of the Ordinary Least Squared (OLS) regression show that the use of highly charged (positive and negative) emotions and personalized posts (first-person singular pronouns) increase likes on the candidates Facebook page. Visual posts (videos and photos) and the use of past tenses do not have a significant effect on post likes. Television mentions decrease the number of likes. The study offers empirical findings contributing to the growing literature on digitally networked participation [33] and support the development of the emerging notion of the new hybrid media system [7] for political communication. It also raises questions as to the relevance of platforms such as Facebook to the democratic process since Facebook users are not necessarily engaging with the content in an organic, democratic way; but instead might be guided to specific content by the Facebook timeline algorithm.

Learning in the wild: coding for learning and practice on Reddit

ABSTRACT Learning on and through social media is becoming a cornerstone of lifelong learning, creating places not only for accessing information, but also for finding other self-motivated learners. Such is the case for Reddit, the online news sharing site that is also a forum for asking and answering questions. We studied learning practices found in ‘Ask’ subreddits AskScience, Ask_Politics, AskAcademia, and AskHistorians to develop a coding schema for informal learning. This paper describes the process of evaluating and defining a workable coding schema, one that started with attention to learning processes associated with discourse, exploratory talk, and conversational dialogue, and ended with including norms and practices on Reddit and the support of communities of inquiry. Our ‘learning in the wild’ coding schema contributes a content analysis schema for learning through social media, and an understanding of how knowledge, ideas, and resources are shared in open, online learning forums.