Twitter reciprocal reply networks exhibit assortativity with respect to happiness

The advent of social media has provided an extraordinary, if imperfect, 'big data' window into the form and evolution of social networks. Based on nearly 40 million message pairs posted to Twitter between September 2008 and February 2009, we construct and examine the revealed social network structure and dynamics over the time scales of days, weeks, and months. At the level of user behavior, we employ our recently developed hedonometric analysis methods to investigate patterns of sentiment expression. We find users' average happiness scores to be positively and significantly correlated with those of users one, two, and three links away. We strengthen our analysis by proposing and using a null model to test the effect of network topology on the assortativity of happiness. We also find evidence that more well connected users write happier status updates, with a transition occurring around Dunbar's number. More generally, our work provides evidence of a social sub-network structure within Twitter and raises several methodological points of interest with regard to social network reconstructions.Comment: 22 pages, 21 figures, 5 tables, In press at the Journal of Computational Scienc

Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter

Individual happiness is a fundamental societal metric. Normally measured through self-report, happiness has often been indirectly characterized and overshadowed by more readily quantifiable economic indicators such as gross domestic product. Here, we examine expressions made on the online, global microblog and social networking service Twitter, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years. Our data set comprises over 46 billion words contained in nearly 4.6 billion expressions posted over a 33 month span by over 63 million unique users. In measuring happiness, we use a real-time, remote-sensing, non-invasive, text-based approach---a kind of hedonometer. In building our metric, made available with this paper, we conducted a survey to obtain happiness evaluations of over 10,000 individual words, representing a tenfold size improvement over similar existing word sets. Rather than being ad hoc, our word list is chosen solely by frequency of usage and we show how a highly robust metric can be constructed and defended.Comment: 27 pages, 17 figures, 3 tables. Supplementary Information: 1 table, 52 figure

On the long and short nulls, modes and interpulse emission of radio pulsar B1944+17

We present a single pulse study of pulsar B1944+17, whose non-random nulls dominate nearly 70% of its pulses and usually occur at mode boundaries. When not in the null state, this pulsar displays four bright modes of emission, three of which exhibit drifting subpulses. B1944+17 displays a weak interpulse whose position relative to the main pulse we find to be frequency independent. Its emission is nearly 100% polarized, its polarization-angle traverse is very shallow and opposite in direction to that of the main pulse, and it nulls approximately two-thirds of the time. Geometric modeling indicates that this pulsar is a nearly aligned rotator whose alpha value is hardly 2 degrees--i.e., its magnetic axis is so closely aligned with its rotation axis that its sightline orbit remains within its conal beam. The star's nulls appear to be of two distinct types: those with lengths less than about 8 rotation periods appear to be pseudonulls--that is, produced by "empty" sightline traverses through the conal beam system; whereas the longer nulls appear to represent actual cessations of the pulsar's emission engine

Human language reveals a universal positivity bias

Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (i ) the words of natural human language possess a universal positivity bias, (ii ) the estimated emotional content of words is consistent between languages under translation, and (iii ) this positivity bias is strongly independent of frequency of word use. Alongside these general regularities, we describe interlanguage variations in the emotional spectrum of languages that allow us to rank corpora. We also show how our word evaluations can be used to construct physical-like instruments for both real-time and offline measurement of the emotional content of large-scale texts

Reply to Garcia et al.: Common mistakes in measuring frequency-dependent word characteristics

We demonstrate that the concerns expressed by Garcia et al. are misplaced, due to (1) a misreading of our findings in [1]; (2) a widespread failure to examine and present words in support of asserted summary quantities based on word usage frequencies; and (3) a range of misconceptions about word usage frequency, word rank, and expert-constructed word lists. In particular, we show that the English component of our study compares well statistically with two related surveys, that no survey design influence is apparent, and that estimates of measurement error do not explain the positivity biases reported in our work and that of others. We further demonstrate that for the frequency dependence of positivity---of which we explored the nuances in great detail in [1]---Garcia et al. did not perform a reanalysis of our data---they instead carried out an analysis of a different, statistically improper data set and introduced a nonlinearity before performing linear regression.Comment: 5 pages, 2 figures, 1 table. Expanded version of reply appearing in PNAS 201

Positivity of the English language

Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is broadly invariant with respect to frequency of word use.Comment: Manuscript: 9 pages, 3 tables, 5 figures; Supplementary Information: 12 pages, 3 tables, 8 figure

Example words for the New York Times as a function of average happiness and usage frequency rank .

<p>Words are centered at their values of and , and angles and colors are only used for the purpose of readability. Each word is a representative of the set of words found in a rectangle of size 0.5 by 375 in and , with all 5000 words located in the background by light gray points. The collapsed distribution at the top matches that shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029484#pone-0029484-g001" target="_blank">Fig. 1</a>.</p