(5 MB), Urban Dictionary Words and Definitions [Kaggle]: Cleaned CSV corpus of 2.6 Million of all Urban Dictionary words, definitions, authors, votes as of May 2016. Formal analysis, In these tweets, Trump often interacted with users as illustrated in example 10: Use of this interactive style gradually decreased over the next few years, until a few months before Trump declared his candidacy, when there was a rapid rise in informality. The mean tweet length per day in the corpus is 17 words, but this rose to 33 words after Twitter increased the character limit for posts from 140 to 280 characters on 2017-11-07. Formal analysis, For example, in terms of the Trump presidency, the Democratic National Committee hack, the New York Times anonymous op-ed, and the fake news crisis are all major news items that are directly linked to collections of online language data. Validation, ... As you can see there are more data points with the label 0 meaning tweets that are not disaster tweets and fewer data points with the label 1 which is tweets that are related to a disaster. Although this style was relatively uncommon for almost four years before Trump declared, it was used in some of his earlier tweets, when he was primarily using Twitter to promote his brand, as illustrated in examples 15 and 16. This hypothesis is supported by previous research on sentiment analysis, which found that Trump ran a more positive campaign than Clinton on Twitter in the ten days before the election, using more positive words and generating a greater positive sentiment around the campaign [15]. Apache Software Foundation Public Mail Archives: all publicly available Apache Software Foundation mail archives as of July 11, 2011 (200 GB), Blog Authorship Corpus: consists of the collected posts of 19,320 bloggers gathered from blogger.com in August 2004. One of these dimensions was interpreted as being associated with a narrative style, contrasting texts exhibiting frequent use of features such as past tense and third person pronouns, which are especially common in genres like fiction and biographies, with texts exhibiting frequent use of features such as present tense and attributive adjectives, which are especially common in non-narrative genres like news broadcasts and official documents. Basically, MDA finds the main dimensions of stylistic variation in a corpus of texts by extracting common patterns of grammatical co-occurrence across the texts through a multivariate statistical analysis of the relative frequencies of a range of grammatical forms (e.g. For instance, examples 19 and 20 have very strong negative coordinates on Dimension 4 and both make unqualified claims: In both examples Trump declares something to be unambiguously true–positive evaluations of his campaign and the stock market–even though these claims were not generally accepted as true at the time. In fact, we see one especially clear yet unexplained inflection point across multiple dimensions around 2015-02-03, not long before Trump formed his exploratory committee. In total, we identified 123 lexical and grammatical features. Contains nearly 15K rows with three contributor judgments per text string. Most Recent Quarterly Refunding Documents. Trump and his team appear to have struck an important balance, which may have helped them navigate their way to victory in the general election. There is also a notable retweet on this day, which is no longer available: Although clearly far from conclusive evidence that Trump decided to run at this time, these tweets, along with the sharp changes in style we observe, are suggestive of a shift in Trump’s political outlook. (Jing Huo, Wenbin Li, Yinghuan Shi, Yang Gao and Hujun Yin) [Before 28/12/19] This result demonstrates one of the advantages of a multidimensional approach to the analysis of stylistic variation: individual texts can be scored highly on multiple dimensions, reflecting the fact that texts, even as short as tweets, can accomplish numerous communicative goals at the same time. For example, spontaneous modes of production (e.g. PLoS ONE 14(9): Other narrative features are also common, including past tense, perfect aspect, and public verbs, which are used to report on completed actions, and progressive verbs, which are used to refer to events in progress [35]. (3 GB), Million News Headlines - ABC Australia [Kaggle]: 1.3 Million News headlines published by ABC News Australia from 2003 to 2017. A red cell indicates that a feature is associated with the positive pole of a dimension, and a blue cell indicates that it is associated with the negative pole. Only the presence of 6 features are associated with the negative pole of Dimension 1, including hashtags and URLs, which often stand alone in Trump’s shortest tweets. Critiques are realised using a range of rhetorical strategies: self-reference to introduce Trump’s alternative, especially in a more positive light than his targets, signalling an “us versus them” dichotomy [80]; modals of necessity to mark the previous actions under attack; passive constructions to emphasise the patient of the act [80]; and rhetorical questions to set up attacks and place blame. This approach is valid, if texts are combined in a principled manner, but it does not allow for variation to be examined at the level of the individual texts, drastically limiting the resolution and meaningfulness of these studies. Su For those who are still curious, I already answered when asked the first time. Dimension 4 shows a relatively simple trend over time (see Figs 4 and 5), with a gradual fall in engagement since 2011, aside from spikes around the time of various seasons of The Apprentice, especially the final season in 2015, not long before Trump would declare. Although the focus of this paper has been on the 2016 campaign, it is also important to understand how the Trump Twitter account has been used as a communication platform by the administration. In fact, one of the clearest shifts in style in the entire corpus occurred once Trump won the presidency: at that point his style across all four dimensions shifted dramatically. Answers corpus from a 10/25/2007 dump, selected for their linguistic properties. From 2009 until 2012, the Trump Twitter account was relatively formal, aside from a spike in 2011 around the time of the Birther controversy. Paper. This need not be the case. (240 MB), Amazon Reviews: Stanford collection of 35 million amazon reviews. On Twitter, Trump gave at least some of the credit to his social media presence: The claim that social media was integral to Trump’s campaign has been supported by several independent studies [13–19]. For example, we know in general that English-language texts written in a more informal style tend to be characterised by relatively frequent use of contractions, interjections, and pronouns, whereas texts written in a more formal style tend to be characterised by relatively infrequent use of these features and relatively frequent use of nouns, prepositions, and determiners [35]. Government policy is to try and make the climate cooler. For instance, examples 7 and 8 have very strong negative coordinates on Dimension 2 and are written in a more formal and expository style, at least for Twitter: The features most strongly associated with these tweets are almost all linked by a more formal style–more informationally dense, composed of complex noun phrases, which generally require careful planning by the author [35]. (65 MB), Identifying key phrases in text: Question/Answer pairs + context; context was judged if relevant to question/answer. You signed in with another tab or window. Has API. In comparison to other major candidates in the 2016 Republican primaries and the 2016 Presidential election, Donald Trump entered the race with a lack of support from politicians in his own party [1–3], the mainstream media [4], and large private donors [5], all of which have traditionally been seen as necessary for a successful campaign [3, 6]. Tweets with positive Dimension 4 coordinates tend to be engaged–not only interacting with other accounts, although that is often the case, but crucially acknowledging the ideas, viewpoints, and statements of others [76].
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