A study (Kramer et al., 2014) was recently published that showed something astonishing — people altered their emotions and moods based upon the presence or absence of other people’s positive (and negative) moods, as expressed on Facebook status updates. The researchers called this effect an “emotional contagion,” because they purported to show that our friends’ words on our Facebook news feed directly affected our own mood. 
 
 Nevermind that the researchers never actually measured anyone’s mood. 
 
 And nevermind that the study has a fatal flaw. One that other research has also overlooked — making all these researchers’ findings a bit suspect. 
 
 Putting aside the ridiculous language used in these kinds of studies (really, emotions spread like a “contagion”?), these kinds of studies often arrive at their findings by conducting language analysis on tiny bits of text. On Twitter, they’re really tiny — less than 140 characters. Facebook status updates are rarely more than a few sentences. The researchers don’t actually measure anybody’s mood. 
 
 So how do you conduct such language analysis, especially on 689,003 status updates? Many researchers turn to an automated tool for this, something called the Linguistic Inquiry and Word Count application (LIWC 2007). This software application is described by its authors as: 
 
 The first LIWC application was developed as part of an exploratory study of language and disclosure (Francis, 1993; Pennebaker, 1993). As described below, the second version, LIWC2007, is an updated revision of the original application. 
 
 Note those dates. Long before social networks were founded, the LIWC was created to analyze large bodies of text — like a book, article, scientific paper, an essay written in an experimental condition, blog entries, or a transcript of a therapy session. Note the one thing all of these share in common — they are of good length, at minimum 400 words. 
 
 Why would researchers use a tool not designed for short snippets of text to, well… analyze short snippets of text? Sadly, it’s because this is one of the few tools available that can process large amounts of text fairly quickly. 
 
 Who Cares How Long the Text is to Measure? 
 
 You might be sitting there scratching your head, wondering why it matters how long the text it is you’re trying to analyze with this tool. One sentence, 140 characters, 140 pages… Why would length matter? 
 
 Length matters because the tool actually isn’t very good at analyzing text in the manner that Twitter and Facebook researchers have tasked it with. When you ask it to analyze positive or negative sentiment of a text, it simply counts negative and positive words within the text under study. For an article, essay or blog entry, this is fine — it’s going to give you a pretty accurate overall summary analysis of the article since most articles are more than 400 or 500 words long. 
 
 For a tweet or status update, however, this is a horrible analysis tool to use. That’s because it wasn’t designed to differentiate — and in fact, can’t differentiate — a negation word in a sentence. 
 
 Let’s look at two hypothetical examples of why this is important. Here are two sample tweets (or status updates) that are not uncommon: 
 
 “I am not happy.” “I am not having a great day.” 
 
 An independent rater or judge would rate these two tweets as negative — they’re clearly expressing a negative emotion. That would be +2 on the negative scale, and 0 on the positive scale. 
 
 But the LIWC 2007 tool doesn’t see it that way. Instead, it would rate these two tweets as scoring +2 for positive (because of the words “great” and “happy”) and +2 for negative (because of the word “not” in both texts). 
 
 That’s a huge difference if you’re interested in unbiased and accurate data collection and analysis. 
 
 And since much of human communication includes subtleties such as this — without even delving into sarcasm, short-hand abbreviations that act as negation words, phrases that negate the previous sentence, emojis, etc. — you can’t even tell how accurate or inaccurate the resulting analysis by these researchers is. Since the LIWC 2007 ignores these subtle realities of informal human communication, so do the researchers. 
 
 Perhaps it’s because the researchers have no idea how bad the problem actually is. Because they’re simply sending all this “big data” into the language analysis engine, without actually understanding how the analysis engine is flawed. Is it 10 percent of all tweets that include a negation word? Or 50 percent? Researchers couldn’t tell you. 
 
 Even if True, Research Shows Tiny Real World Effects 
 
 Which is why I have to say that even if you believe this research at face value despite this huge methodological problem, you’re still left with research showing ridiculously small correlations that have little to no meaning to ordinary users. 
 
 For instance, Kramer et al. (2014) found a 0.07% — that’s not 7 percent, that’s 1/15th of one percent!! — decrease in negative words in people’s status updates when the number of negative posts on their Facebook news feed decreased. Do you know how many words you’d have to read or write before you’ve written one less negative word due to this effect? Probably thousands. 
 
 This isn’t an “effect” so much as a statistical blip that has no real-world meaning. The researchers themselves acknowledge as much, noting that their effect sizes were “small (as small as d = 0.001).” They go on to suggest it still matters because “small effects can have large aggregated consequences” citing a Facebook study on political voting motivation by one of the same researchers, and a 22 year old argument from a psychological journal. 
 
 But they contradict themselves in the sentence before, suggesting that emotion “is difficult to influence given the range of daily experiences that influence mood.” Which is it? Are Facebook status updates significantly impacting individual’s emotions, or are emotions not so easily influenced by simply reading other people’s status updates?? 
 
 Despite all of these problems and limitations, none of it stops the researchers in the end from proclaiming, “These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks.” Again, no matter that they didn’t actually measure a single person’s emotions or mood states, but instead relied on a flawed assessment measure to do so. 
 
 What the Facebook researchers clearly show, in my opinion, is that they put too much faith in the tools they’re using without understanding — and discussing — the tools’ significant limitations. 
 
 Reference 
 
 Kramer, ADI, Guillory, JE, Hancock, JT. (2014). Experimental evidence of massive-scale emotional contagion through social networks. PNAS. www.pnas.org/cgi/doi/10.1073/pnas.1320040111 
 
 Footnotes: ||||| * Updated since first published. 
 
 This weekend, the Internet discovered a study published earlier this month in an academic journal that recounted how a Facebook data scientist, along with two university researchers, turned 689,003 users' New Feeds positive or negative to see if it would elate or depress them. The purpose was to find out if emotions are "contagious" on social networks. (They are, apparently.) The justification for subjecting unsuspecting users to the psychological mind game was that everyone who signs up for Facebook agrees to the site's "Data Use Policy," which has a little line about how your information could be used for "research." Some people are pretty blase about the study, their reaction along the lines of, "Dude. Facebook and advertisers manipulate us all the time. NBD." Others, especially in the academic environment, are horrified that Facebook thinks that the little clause in the 9,045-word ToS counts as "informed consent" from a user to take part in a psychological experiment, and that an ethics board reportedly gave that interpretation a thumbs up, which led most academic commentators' jaws to hit the floor. 
 
 Update (6:55 p.m.): A source familiar with the matter says the study was approved through an internal review process at Facebook, not through a university Institutional Review Board. Update (10:57 p.m.): Professor Susan Fiske, the editor at the Proceedings of the National Academy of Sciences for the study's publication, says the data analysis was approved by a Cornell Institutional Review Board but not the data collection. "Their revision letter said they had Cornell IRB approval as a 'pre-existing dataset' presumably from Facebook, who seems to have reviewed it as well in some unspecified way," writes Fiske by email. The Cornell IRB has not yet responded to a media request. (Update 6/30/14): Cornell released a statement Monday morning saying its IRB passed on reviewing the study because the part involving actual humans was done by Facebook not by the Cornell researcher involved in the study. Though it that researcher did help design the study -- based on the notes about the roles of the authors in PNAS and Cornell's statement that the academics were involved in "initial discussions" about the study -- so this seems a bit disingenuous. 
 
 The larger debate is about what companies can do to their users without asking them first or telling them about it after. I asked Facebook yesterday what the review process was for conducting the study in January 2012, and its response reads a bit tone deaf. The focus is on whether the data use was appropriate rather than on the ethics of emotionally manipulating users to have a crappy day for science. That may be because Facebook was responding to a privacy reporter. 
 
 "This research was conducted for a single week in 2012 and none of the data used was associated with a specific person's Facebook account," says a Facebook spokesperson. "We do research to improve our services and to make the content people see on Facebook as relevant and engaging as possible. A big part of this is understanding how people respond to different types of content, whether it's positive or negative in tone, news from friends, or information from pages they follow. We carefully consider what research we do and have a strong internal review process. There is no unnecessary collection of people's data in connection with these research initiatives and all data is stored securely." 
 
 It's particularly fascinating to me that Facebook puts this in the "research to improve our services" category, as opposed to "research for academic purposes" category. One usable takeaway in the study was that taking all emotional content out of a person's feed caused a "withdrawal effect." Thus Facebook now knows it should subject you to emotional steroids to keep you coming back. It makes me wonder what other kind of psychological manipulation users are subjected to that they never learn about because it isn't published in an academic journal. 
 
 Mid-day on Sunday, Facebook data scientist Adam Kramer who helped run the study also commented on it through a post on his Facebook page. Available in full below, Kramer says, essentially, that the reason he and his co-researchers did this study was to make Facebook better. "[W]e care about the emotional impact of Facebook and the people that use our product," he writes. "We felt that it was important to investigate the common worry that seeing friends post positive content leads to people feeling negative or left out. At the same time, we were concerned that exposure to friends' negativity might lead people to avoid visiting Facebook." 
 
 Kramer sounded a wee bit apologetic: "In hindsight, the research benefits of the paper may not have justified all of this anxiety." He said that Facebook is working on improving its internal review practices for approving experiments like this and that it will "incorporate what we’ve learned from the reaction to this paper." 
 
 Based on Kramer's remarks and Facebook's statement, it's evident that the company still doesn't understand the core concern of critics: that testing whether users' emotions can be manipulated through content curation is creepy. 
 
 This gives more fodder to academic Ryan Calo who has argued that companies need to get their psychological studies of users vetted in some way that echoes what happens in the academic context. When universities conduct studies on people, they have to run them by an ethics board first to get approval — ethics boards that were mandated by the government in the 1970s because scientists were getting too creepy in their experiments, getting subjects to think they were shocking someone to death in order to study obedience, for example. Interestingly, the Facebook "emotional contagion" project had funding from the government -- the Army Research Office -- according to a Cornell profile of one of the academic researchers involved. Update (12:58 a.m.): Cornell has updated that profile to say there was no Army funding. 
 
 Before this story broke, Betsy Haibel wrote a relevant post that linguistically elevated the stakes by calling companies' assumption of consent from users as corporate rape culture. "The tech industry does not believe that the enthusiastic consent of its users is necessary," wrote Haibel. "The tech industry doesn't even believe in requiring affirmative consent." 
 
 When I signed up for 23andMe -- a genetic testing service -- it asked if I was willing to be part of "23andWe," which would allow my genetic material to be part of research studies. I had to affirmatively check a box to say I was okay with that. As I suggested when I wrote about this yesterday, I think Facebook should have something similar. While many users may already expect and be willing to have their behavior studied -- and while that may be warranted with "research" being one of the 9,045 words in the data use policy -- they don't expect that Facebook will actively manipulate their environment in order to see how they react. That's a new level of experimentation, turning Facebook from a fishbowl into a petri dish, and it's why people are flipping out about this. 
 
 ---- 
 
 FULL STATEMENT FROM ADAM KRAMER, OF FACEBOOK 
 
 Adam D. I. Kramer in Floyd, VA 
 
 OK so. A lot of people have asked me about my and Jamie and Jeff's recent study published in PNAS, and I wanted to give a brief public explanation. The reason we did this research is because we care about the emotional impact of Facebook and the people that use our product. We felt that it was important to investigate the common worry that seeing friends post positive content leads to people feeling negative or left out. At the same time, we were concerned that exposure to friends' negativity might lead people to avoid visiting Facebook. We didn't clearly state our motivations in the paper. 
 
 Regarding methodology, our research sought to investigate the above claim by very minimally deprioritizing a small percentage of content in News Feed (based on whether there was an emotional word in the post) for a group of people (about 0.04% of users, or 1 in 2500) for a short period (one week, in early 2012). Nobody's posts were "hidden," they just didn't show up on some loads of Feed. Those posts were always visible on friends' timelines, and could have shown up on subsequent News Feed loads. And we found the exact opposite to what was then the conventional wisdom: Seeing a certain kind of emotion (positive) encourages it rather than suppresses is. 
 
 And at the end of the day, the actual impact on people in the experiment was the minimal amount to statistically detect it -- the result was that people produced an average of one fewer emotional word, per thousand words, over the following week. 
 
 The goal of all of our research at Facebook is to learn how to provide a better service. Having written and designed this experiment myself, I can tell you that our goal was never to upset anyone. I can understand why some people have concerns about it, and my coauthors and I are very sorry for the way the paper described the research and any anxiety it caused. In hindsight, the research benefits of the paper may not have justified all of this anxiety. 
 
 While we’ve always considered what research we do carefully, we (not just me, several other researchers at Facebook) have been working on improving our internal review practices. The experiment in question was run in early 2012, and we have come a long way since then. Those review practices will also incorporate what we’ve learned from the reaction to this paper. ||||| Significance We show, via a massive (N = 689,003) experiment on Facebook, that emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. We provide experimental evidence that emotional contagion occurs without direct interaction between people (exposure to a friend expressing an emotion is sufficient), and in the complete absence of nonverbal cues. 
 
 Abstract Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others’ positive experiences constitutes a positive experience for people. 
 
 Emotional states can be transferred to others via emotional contagion, leading them to experience the same emotions as those around them. Emotional contagion is well established in laboratory experiments (1), in which people transfer positive and negative moods and emotions to others. Similarly, data from a large, real-world social network collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks as well (2, 3). 
 
 The interpretation of this network effect as contagion of mood has come under scrutiny due to the study’s correlational nature, including concerns over misspecification of contextual variables or failure to account for shared experiences (4, 5), raising important questions regarding contagion processes in networks. An experimental approach can address this scrutiny directly; however, methods used in controlled experiments have been criticized for examining emotions after social interactions. Interacting with a happy person is pleasant (and an unhappy person, unpleasant). As such, contagion may result from experiencing an interaction rather than exposure to a partner’s emotion. Prior studies have also failed to address whether nonverbal cues are necessary for contagion to occur, or if verbal cues alone suffice. Evidence that positive and negative moods are correlated in networks (2, 3) suggests that this is possible, but the causal question of whether contagion processes occur for emotions in massive social networks remains elusive in the absence of experimental evidence. Further, others have suggested that in online social networks, exposure to the happiness of others may actually be depressing to us, producing an “alone together” social comparison effect (6). 
 
 Three studies have laid the groundwork for testing these processes via Facebook, the largest online social network. This research demonstrated that (i) emotional contagion occurs via text-based computer-mediated communication (7); (ii) contagion of psychological and physiological qualities has been suggested based on correlational data for social networks generally (7, 8); and (iii) people’s emotional expressions on Facebook predict friends’ emotional expressions, even days later (7) (although some shared experiences may in fact last several days). To date, however, there is no experimental evidence that emotions or moods are contagious in the absence of direct interaction between experiencer and target. 
 
 On Facebook, people frequently express emotions, which are later seen by their friends via Facebook’s “News Feed” product (8). Because people’s friends frequently produce much more content than one person can view, the News Feed filters posts, stories, and activities undertaken by friends. News Feed is the primary manner by which people see content that friends share. Which content is shown or omitted in the News Feed is determined via a ranking algorithm that Facebook continually develops and tests in the interest of showing viewers the content they will find most relevant and engaging. One such test is reported in this study: A test of whether posts with emotional content are more engaging. 
 
 The experiment manipulated the extent to which people (N = 689,003) were exposed to emotional expressions in their News Feed. This tested whether exposure to emotions led people to change their own posting behaviors, in particular whether exposure to emotional content led people to post content that was consistent with the exposure—thereby testing whether exposure to verbal affective expressions leads to similar verbal expressions, a form of emotional contagion. People who viewed Facebook in English were qualified for selection into the experiment. Two parallel experiments were conducted for positive and negative emotion: One in which exposure to friends’ positive emotional content in their News Feed was reduced, and one in which exposure to negative emotional content in their News Feed was reduced. In these conditions, when a person loaded their News Feed, posts that contained emotional content of the relevant emotional valence, each emotional post had between a 10% and 90% chance (based on their User ID) of being omitted from their News Feed for that specific viewing. It is important to note that this content was always available by viewing a friend’s content directly by going to that friend’s “wall” or “timeline,” rather than via the News Feed. Further, the omitted content may have appeared on prior or subsequent views of the News Feed. Finally, the experiment did not affect any direct messages sent from one user to another. 
 
 Posts were determined to be positive or negative if they contained at least one positive or negative word, as defined by Linguistic Inquiry and Word Count software (LIWC2007) (9) word counting system, which correlates with self-reported and physiological measures of well-being, and has been used in prior research on emotional expression (7, 8, 10). LIWC was adapted to run on the Hadoop Map/Reduce system (11) and in the News Feed filtering system, such that no text was seen by the researchers. As such, it was consistent with Facebook’s Data Use Policy, to which all users agree prior to creating an account on Facebook, constituting informed consent for this research. Both experiments had a control condition, in which a similar proportion of posts in their News Feed were omitted entirely at random (i.e., without respect to emotional content). Separate control conditions were necessary as 22.4% of posts contained negative words, whereas 46.8% of posts contained positive words. So for a person for whom 10% of posts containing positive content were omitted, an appropriate control would withhold 10% of 46.8% (i.e., 4.68%) of posts at random, compared with omitting only 2.24% of the News Feed in the negativity-reduced control. 
 
 The experiments took place for 1 wk (January 11–18, 2012). Participants were randomly selected based on their User ID, resulting in a total of ∼155,000 participants per condition who posted at least one status update during the experimental period. 
 
 For each experiment, two dependent variables were examined pertaining to emotionality expressed in people’s own status updates: the percentage of all words produced by a given person that was either positive or negative during the experimental period (as in ref. 7). In total, over 3 million posts were analyzed, containing over 122 million words, 4 million of which were positive (3.6%) and 1.8 million negative (1.6%). 
 
 If affective states are contagious via verbal expressions on Facebook (our operationalization of emotional contagion), people in the positivity-reduced condition should be less positive compared with their control, and people in the negativity-reduced condition should be less negative. As a secondary measure, we tested for cross-emotional contagion in which the opposite emotion should be inversely affected: People in the positivity-reduced condition should express increased negativity, whereas people in the negativity-reduced condition should express increased positivity. Emotional expression was modeled, on a per-person basis, as the percentage of words produced by that person during the experimental period that were either positive or negative. Positivity and negativity were evaluated separately given evidence that they are not simply opposite ends of the same spectrum (8, 10). Indeed, negative and positive word use scarcely correlated [r = −0.04, t(620,587) = −38.01, P < 0.001]. 
 
 We examined these data by comparing each emotion condition to its control. After establishing that our experimental groups did not differ in emotional expression during the week before the experiment (all t < 1.5; all P > 0.13), we examined overall posting rate via a Poisson regression, using the percent of posts omitted as a regression weight. Omitting emotional content reduced the amount of words the person subsequently produced, both when positivity was reduced (z = −4.78, P < 0.001) and when negativity was reduced (z = −7.219, P < 0.001). This effect occurred both when negative words were omitted (99.7% as many words were produced) and when positive words were omitted (96.7%). An interaction was also observed, showing that the effect was stronger when positive words were omitted (z = −77.9, P < 0.001). 
 
 As such, direct examination of the frequency of positive and negative words would be inappropriate: It would be confounded with the change in overall words produced. To test our hypothesis regarding emotional contagion, we conducted weighted linear regressions, predicting the percentage of words that were positive or negative from a dummy code for condition (experimental versus control), weighted by the likelihood of that person having an emotional post omitted from their News Feed on a given viewing, such that people who had more content omitted were given higher weight in the regression. When positive posts were reduced in the News Feed, the percentage of positive words in people’s status updates decreased by B = −0.1% compared with control [t(310,044) = −5.63, P < 0.001, Cohen’s d = 0.02], whereas the percentage of words that were negative increased by B = 0.04% (t = 2.71, P = 0.007, d = 0.001). Conversely, when negative posts were reduced, the percent of words that were negative decreased by B = −0.07% [t(310,541) = −5.51, P < 0.001, d = 0.02] and the percentage of words that were positive, conversely, increased by B = 0.06% (t = 2.19, P < 0.003, d = 0.008). 
 
 The results show emotional contagion. As Fig. 1 illustrates, for people who had positive content reduced in their News Feed, a larger percentage of words in people’s status updates were negative and a smaller percentage were positive. When negativity was reduced, the opposite pattern occurred. These results suggest that the emotions expressed by friends, via online social networks, influence our own moods, constituting, to our knowledge, the first experimental evidence for massive-scale emotional contagion via social networks (3, 7, 8), and providing support for previously contested claims that emotions spread via contagion through a network. 
 
 Fig. 1. Mean number of positive (Upper) and negative (Lower) emotion words (percent) generated people, by condition. Bars represent standard errors. 
 
 These results highlight several features of emotional contagion. First, because News Feed content is not “directed” toward anyone, contagion could not be just the result of some specific interaction with a happy or sad partner. Although prior research examined whether an emotion can be contracted via a direct interaction (1, 7), we show that simply failing to “overhear” a friend’s emotional expression via Facebook is enough to buffer one from its effects. Second, although nonverbal behavior is well established as one medium for contagion, these data suggest that contagion does not require nonverbal behavior (7, 8): Textual content alone appears to be a sufficient channel. This is not a simple case of mimicry, either; the cross-emotional encouragement effect (e.g., reducing negative posts led to an increase in positive posts) cannot be explained by mimicry alone, although mimicry may well have been part of the emotion-consistent effect. Further, we note the similarity of effect sizes when positivity and negativity were reduced. This absence of negativity bias suggests that our results cannot be attributed solely to the content of the post: If a person is sharing good news or bad news (thus explaining his/her emotional state), friends’ response to the news (independent of the sharer’s emotional state) should be stronger when bad news is shown rather than good (or as commonly noted, “if it bleeds, it leads;” ref. 12) if the results were being driven by reactions to news. In contrast, a response to a friend’s emotion expression (rather than news) should be proportional to exposure. A post hoc test comparing effect sizes (comparing correlation coefficients using Fisher’s method) showed no difference despite our large sample size (z = −0.36, P = 0.72). 
 
 We also observed a withdrawal effect: People who were exposed to fewer emotional posts (of either valence) in their News Feed were less expressive overall on the following days, addressing the question about how emotional expression affects social engagement online. This observation, and the fact that people were more emotionally positive in response to positive emotion updates from their friends, stands in contrast to theories that suggest viewing positive posts by friends on Facebook may somehow affect us negatively, for example, via social comparison (6, 13). In fact, this is the result when people are exposed to less positive content, rather than more. This effect also showed no negativity bias in post hoc tests (z = −0.09, P = 0.93). 
 
 Although these data provide, to our knowledge, some of the first experimental evidence to support the controversial claims that emotions can spread throughout a network, the effect sizes from the manipulations are small (as small as d = 0.001). These effects nonetheless matter given that the manipulation of the independent variable (presence of emotion in the News Feed) was minimal whereas the dependent variable (people’s emotional expressions) is difficult to influence given the range of daily experiences that influence mood (10). More importantly, given the massive scale of social networks such as Facebook, even small effects can have large aggregated consequences (14, 15): For example, the well-documented connection between emotions and physical well-being suggests the importance of these findings for public health. Online messages influence our experience of emotions, which may affect a variety of offline behaviors. And after all, an effect size of d = 0.001 at Facebook’s scale is not negligible: In early 2013, this would have corresponded to hundreds of thousands of emotion expressions in status updates per day. 
 
 Acknowledgments We thank the Facebook News Feed team, especially Daniel Schafer, for encouragement and support; the Facebook Core Data Science team, especially Cameron Marlow, Moira Burke, and Eytan Bakshy; plus Michael Macy and Mathew Aldridge for their feedback. Data processing systems, per-user aggregates, and anonymized results available upon request. 
 
 Footnotes Author contributions: A.D.I.K., J.E.G., and J.T.H. designed research; A.D.I.K. performed research; A.D.I.K. analyzed data; and A.D.I.K., J.E.G., and J.T.H. wrote the paper. 
 
 The authors declare no conflict of interest. 
 
 This article is a PNAS Direct Submission. 
 
 Freely available online through the PNAS open access option. ||||| BE CAREFUL you don't catch those Facebook blues. Feelings, like viruses, can spread through online social networks. 
 
 A face-to-face encounter with someone who is sad or cheerful can leave us feeling the same way. This emotional contagion has been shown to last anywhere from a few seconds to weeks. 
 
 A team of researchers, led by Adam Kramer at Facebook in Menlo Park, California, was curious to see if this phenomenon would occur online. To find out, they manipulated which posts showed up on the news feeds of more than 600,000 Facebook users. For one week, some users saw fewer posts with negative emotional words than usual, while others saw fewer posts with positive ones. 
 
 Digital emotions proved somewhat contagious, too. People were more likely to use positive words in Facebook posts if they had been exposed to fewer negative posts throughout the week, and vice versa. The effect was significant, though modest (PNAS, doi.org/tcg). 
 
 Ke Xu of Beihang University in Beijing has studied emotional contagion on Chinese social networks. He says Kramer's work shows that we don't need to interact in person to influence someone's feelings. 
 
 This article appeared in print under the headline "Even online, emotions can be contagious" 
 
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– A study that altered News Feeds on Facebook claims to show that even online emotions are contagious, NPR reports—but the real story may be that Facebook manipulated News Feeds at all. In the study, researchers played with more than 600,000 users' feeds for a week in 2012, showing some people more positive words and others more negative ones, reports New Scientist. Well, those who saw fewer negative words used more positive ones in their own status updates, and vice versa. The researchers dubbed it "emotional contagion," meaning the News Feeds affected users' feelings—but John Grohol at PychCentral is rolling his eyes, big time. He not only questions the methodology of using software to track words in posts (how would it evaluate "I am not happy," for example?) but also notes that researchers found only .07% fewer negative words in status updates from Facebook users who saw more positive News Feeds. "This isn’t an 'effect' so much as a statistical blip that has no real-world meaning," writes Grohol. And should Facebook users even be subjected to this kind of experiment? The Verge reports that it jibes with Facebook's terms of use, but some critics, especially in academic circles, are "horrified" that Facebook thinks a clause in its 9,045-word ToS lets the company subject users to a "psychological experiment," reports Forbes.