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They can also search on anything—really, anything—that catches their fancy to find other blogs or posts. Abramson says the site will likely change and grow a lot as it evolves beyond just an NSFW Tumblr refuge, and a name change is also coming. Sharesome gets content in your face even sooner. It features something like a Facebook news feed of the most popular posts—regardless whether or not you follow the posters. Many posters are amateurs with just a handful of followers, offering free content that is sometimes adorably awkward.

But those with hundreds or thousands of followers typically use their profile as a teaser with links to other sites where they sell the goods. We will also re-enable promoted posts and we will be adding more options. Abramson says that newTumbl has about a dozen ideas for raising revenue, which will start emerging in Q4. He declined to discuss monetization strategies on the record, but said that they will be based on providing users the ability to earn money for their blogs.

Financial self-sufficiency has slowed the growth of another emerging network, Pillowfort. It opened February as a general-interest site in the mold of Tumblr and the earlys version of LiveJournal.

Pillowfort held a second Kickstarter in August , but really took off with the Tumblr NSFW ban because of its liberal content policies. Pillowfort has about 47, members, but its slow growth is deliberate.

The site is working on modest ways to bring in money—such as extra blog-customization options—that reflect more of an intimate, user-supported community than a mega entertainment site. Users will also have to pay for uploads greater than a few megabytes. They can already embed any kinds of videos, including porn, from other sites. The internet is for porn—and cats and comic books and many other things—at Pillowfort.

It also fails to deliver actionable evidence to policymakers who need to decide whether to encourage or discourage media use 11 , Here, we present such evidence. Media effects can occur on different levels In the case of new media, this general level is represented by screen time 10 , 14 , Subsequently, researchers have studied new media with increasing nuance. They have come to understand that the motivation of users is just as important as the content they engage with 3 , 5 , 14 , For example, users might compare themselves to others on social media; depending on their motivation, that comparison can make them feel better or worse This level of nuance is critical.

However, it must build upon a robust understanding of broad, net effects. An investigation of this broad effect is lacking for more traditional media. Consequently, we cannot compare net effects of social media to those of traditional media. That comparison is important because societal discourse often takes a form of technological determinism 12 for granted: People are helpless in the face of social media and attention demanding notifications, but benefit from traditional media, such as reading books 1.

Therefore, our first research question asked about the effects of media use on well-being over a broad range of traditional media.

Dominated for a long time by cross-sectional work, recent longitudinal studies have begun adding nuance to the analysis of net screen time effects 15 , For one, they distinguish within-person and between-person relations. Between-person relations represent stable differences, but not effects; within-person relations can represent effects 19 , depending on whether there are time-varying confounders 20 , Therefore, several scholars have recommended applying this distinction to the study of media effects 16 , Second, researchers routinely acknowledge that it is unlikely that screen time affects well-being, but not vice versa.

Therefore, most work now models reciprocal relations. Between-person relations between screen time and well-being are negative, but small, with those reporting higher technology use also showing slightly lower well-being 8 , 9 , 23 , On the within-person level, effects are negligible: If a person uses technology more than they usually do, any effects on well-being are too small to matter practically 8 , 9 , 25 , 26 , 27 , These negligible effects appear to be reciprocal 8 , 9 , Unfortunately, we do not have such insights for traditional media.

Therefore, our second research question asked about the reciprocal effects between media use and well-being, distinguishing between-person relations from potential within-person effects.

Technological determinism also contributes to a focus on researching only how much a person uses technology, but rarely whether someone uses the technology in the first place. An implicit linear dose—response model underlies this focus: Research asks how much technology will yield what amount of harm 30 , But the decision whether to use a medium or not is most likely a different psychological process than the sheer amount of time people use that medium for.

Deciding to read a book might be good for our well-being, regardless of whether we read for ten minutes or two hours. Conversely, it might not matter whether we pick up a book if we only spend a few minutes reading. So far, research has treated the step from zero to one minute as similar to the step from to min, even though use versus nonuse likely has larger consequences than merely spending a minute more with a medium we already use a lot. The few studies looking at users versus nonusers are in a similar state as the research on screen time five years ago.

Although they reveal some interesting differences, they are mostly cross-sectional 32 , Whereas researchers study time spent with media with increasing nuance by employing longitudinal designs and separating between- and within-person levels, we lack that nuance for use versus nonuse. We are aware of only one study that reports a small positive within-person association between using versus not using social media and well-being Therefore, our third research question asked about the different effect of use versus nonuse and time spent with a medium.

The question of how much screen time will harm people has also overshadowed another important question: On what facet of well-being should we expect effects and how long does it take for media use to affect well-being? Most research has relied on relatively broad and stable indicators of well-being, a component of mental health, that address evaluative, cognitive well-being, such as life satisfaction.

Because life satisfaction is remarkably stable over longer periods of time, it is questionable whether media use can produce changes strong enough to impact how people evaluate their lives Cohort studies with yearly lags 9 , 28 , 35 or lags of several months 36 , 37 have produced mostly null findings on the within-person level.

Instead, researchers have argued that media use should impact the affective component of well-being, such as the positive or negative affect that people experience 16 , The question of what type of well-being media use influences is therefore closely tied to the lag in measurement.

If media use indeed has an effect on well-being, we should observe it in the short-term and on affect. Life satisfaction might be too stable—or the net influence of media use too small—to change in the short-term; alternatively, media effects might be too weak to change life satisfaction even in the long-term. For example, there is strong evidence that social media, internet, and TV use do not impact life satisfaction to a meaningful degree over several years 9 , On the flip side, even recent studies using half- hourly lags found no meaningful effect of social media use on affect 34 , 38 , Instead, small media effects may accumulate in intermediate time frames, such that we experience an effect on well-being only after enough use episodes For example, binging TV shows over a week may only have small, fleeting effects right after watching, but could accumulate and fully unfold its effects by the end of the week.

The data set we analyzed allowed us to test this proposition: It had a relatively short time lag of one week and measured both affect and life satisfaction. Therefore, our fourth research question asked about the effect of media use on different indicators of well-being in a relatively short time span. We explored the question of the effects of diverse forms of media use on well-being and vice versa by analyzing an existing data set of a nationally representative cohort of people living in the UK over six weekly measurements during the first national lockdown April and May We had four research questions: First, we tested the effects of a wider range of seven more traditional media : music, TV, films, video games, e- books, digital magazines, and audiobooks.

Second, we separated between-person relations from within-person effects. Third, we analyzed both use versus nonuse and time spent using a medium. Fourth, to get a better understanding of which well-being concepts media use most likely affects, we compared effects on both affect i.

Together, these steps deliver a comprehensive base of evidence over a range of traditional media that is lacking from the literature. We did not preregister a processing and analysis plan for secondary data The analyses testing our research questions showed that estimates we observed were generally small; between-person relations but rarely within-person effect; mostly for use versus nonuse and not time spent with a medium; and for affect, not life satisfaction.

Figures 1 and 2 present an overview of the results. Note that both facets in the top-row in both figures represent the same theoretical effects. However, they were obtained from different models, explaining their small differences.

This Figure shows the reciprocal effects between using versus not using a medium and well-being. Points represent the mean of the posterior distribution of the effects.

On the left-hand column, coefficients are of the Gaussian models; they represent an unstandardized estimate on the 0 to 10 well-being scale.

On the right, coefficients are of the hurdle gamma model, meaning they represent odds of using a medium at all hurdle part and time spent using a medium more gamma part. The top part shows between-person relations. The bottom part shows within-person effects. Estimates are grouped by the well-being measures, affect versus life satisfaction.

This Figure shows the reciprocal effects between time spent using a medium and well-being. Note that the range on the x-axis is different from Fig.

Before we turn to the research questions, we provide an example that a showcases how to interpret the model estimates, and b demonstrates the complexity of media effects. In Fig. Across the entire sample and all waves, the model estimated that someone who listens to music, compared to someone who does not listen to music, reports feeling somewhat worse on affect, but not on life satisfaction on the raw 0 to 10 scale.

That correlation is mirrored on the top right that shows relations between affect and life satisfaction, across all waves, and whether someone listens to music versus not.

Mirroring the left-hand columns, someone who feels one point better than someone else on the 0 to 10 affect measure has lower odds of listening to music compared to someone else. More importantly, the bottom left shows within-person effects of listening to music—the most relevant outcome of our models because they inform us about media effects rather than between-person correlations.

Going from not listening to music to listening to music makes a person feel slightly better by the end of the week. Conversely on the bottom right , if a person feels one point better on affect than they typically do at the beginning of the week, their increase in affect does not increase their odds of listening to music in that week.

The top left corner shows that one hour more music listening than someone else is only weakly related to lower well-being affect ; conversely, scoring one point higher on well-being affect than someone else is only weakly related to lower odds of spending more time listening to music.

At the within-person level bottom left , when a person listens to one hour more than they typically do, their listening makes them feel slightly better, but the posterior included zero as well as negative effects. Likewise, if someone scores one point higher on the affect scale than they typically do, their increase in affect does not increase their odds of listening to more music bottom right. Addressing our first research question, between-person differences of users versus non-users were comparable across all media—mostly in direction of the difference, but also in size.

People engaging with music, TV, films, and video games felt generally worse than those who did not engage with those media. Those reading books or magazines or listening to audiobooks did not feel better or worse than those who did not. Again, these differences represent correlations. It is just as possible that people who feel bad generally turn to music, TV, films, and video games, but it matters little how a person feels when they choose to read books, magazines, or listen to audiobooks.

Even effects whose posterior distribution excluded zero, as was the case for TV and music use versus nonuse, were small. The same goes for the other direction of the effect: Feeling better than usual did rarely lead to a change in the odds of picking up a new medium or engaging more with an old one. That lack of a change applied across all of the media types. Results concerning our second research question show that most relevant estimates happen on the between-person level.

These differences represent stable differences between people across all waves. They represent correlations and not causal effects. They show mostly small negative relations between media use and well-being. More specifically, these relations appear to be driven by differences between using versus not using a medium, not by how much time people spend with that medium. Those people who use a medium, compared to people who do not use the medium, in general feel worse.

Again, this conclusion is not causal, and it works both ways: In general, those who feel worse than others have higher odds of using a medium. More importantly, on the within-level, very few posterior distributions excluded a null effect. Those that did represented small effects e. To test our third research question, we inspected general differences between using versus not using a medium and time spent with a medium.

We see that most effects whose posterior excludes zero occur for whether a person uses a medium and less so by how much time they spend engaging with that medium.

These effects are also generally larger and less certain than effects of the time spent with a medium. Most coefficients describing effects on and of time spent with a medium are extremely small. Even if their posterior excludes zero, we can be relatively certain—conditional on the model and the data generating process we assumed—that the true underlying effect is small to negligible.

For example, going from not watching TV to watching TV results in about a third of a point increase by the end of the week on the eleven-point affect scale. But one hour more TV time than a person typically watches results in a hundredths of a point decrease by the end of the week, and the posterior of that effect includes zero.

Addressing our fourth research question, almost all differences we observed on the between-person level were in affect, not in life satisfaction. In other words, users and nonusers of media differ on how anxious and happy they feel across the study period of six weeks i.

They differed less on the degree to which they evaluate their lives in general. Even though most posterior distributions of the between-person differences on life-satisfaction were negative, they all included the null effect as a plausible value that represented the true underlying difference conditional on the model. Similarly, the few within-person effects whose posterior excluded the null effect were on affect. For example, those who picked up watching TV reported higher affect by the end of the week, but not higher life satisfaction.

New media like social networking sites allegedly exert an almost addictive effect on their users, whereas traditional media like books are considered a beneficial pastime. However, the alleged benefits of traditional media remain speculative without much evidence of their effects on well-being.

First, we investigated media effects across a wide range of seven traditional media. Second, in a reciprocal analysis we separated within-person effects from between-person relations. Third, we treated use versus nonuse and time spent with a medium as different processes. Last, we analyzed data with a shorter time lag than most previous work, testing which facets of well-being are affected most by media use. Our findings provide little cause for alarm: Almost all differences were between users and nonusers on a stable between-person level, with small to negligible within-person effects in either direction.

The few effects we found were comparable across media and largely on the more volatile affective well-being, rather than more stable life satisfaction. Distinguishing use versus nonuse and time spent with a medium proved important. Most differences we observed were on the between-person level between users and nonusers. Likewise, the few small within-person effects incompatible with zero as the true effect occurred when a person went from not using a medium in one week to using a medium the next week.

The time spent with a medium played a negligible role. In other words, our findings are not in line with the dominant linear dose—response model that often implicitly assumes that going from zero use to one minute of use has the same effect as going from one hour of use to one hour and one minute of use 30 , Instead, the decision to use a medium appears to represent a threshold; once a user crosses that threshold, the amount of time they spend with a medium is of little consequence for their well-being.

This conclusion almost exclusively applies to the between-person level: Media users i. However, those differences were around a third of a point on an eleven-point scale. On the within-person level, going from nonuse to use had generally small effects across media.

The effects of time spent with a medium were even smaller. Our results speak against pronounced causal effects—neither positive nor negative—of media use during the week on well-being by the end of the week. The pattern of small between-person relations but negligible within-person effects aligns with previous research on new media 8 , 9 , There were no substantial differences across the seven traditional media types we studied. E- book and digital magazine readers as well as audiobooks listeners did not experience less affective well-being unlike those engaging with music, TV, films, and games.

That finding applies in both directions: Those with lower well-being were more likely to engage with these media. However, those differences all but disappeared on the within-person level, with most effect sizes close to a null effect. Only TV and music use versus nonuse on the within-level showed a small positive effect on affect.

Together, the results stand in contrast to public opinion, where traditional media are valued highly 1 , It appears the broad, net effect of traditional media is similar to that of social media: too close to zero to be perceived by media users Our study also addresses the choice of time lag and well-being indicator.

If anything, media use should influence short-term affect. Our results deliver weak evidence that this distinction also applies to traditional media. The few differences we observed appeared almost exclusively on the more volatile positive affect, not stable life satisfaction. These results align well with research that shows little to no long-term effects of new media on life satisfaction 9 , 27 , 28 , We deliver evidence that traditional media are unlikely to impact life satisfaction within the intermediate time frame of one week that we studied.

At the same time, the few effects on affect were small, similar to research on social media with much shorter time lags 34 , 38 , Either we missed the optimal time lag after which the effects disappeared 40 or net effects of traditional media are indeed negligible.

What do our results mean? The straightforward answer is: The effect of traditional media on well-being is too small to matter. However, such an answer might overlook important nuance. First, throughout this manuscript, we have spoken of between-person relations, but of within-person effects.

As we have noted, within-person relations can be effects under the assumption that there are no time-varying confounders. Therefore, what we call effects is causal only under that assumption 20 , 21 , There might well be time-varying factors that mask a true effect For example, spending time using media may have a negative effect on well-being which gets balanced out by an indirect positive effect via less time worrying.

Similarly, a stable confounder e. Alternatively, people who do not feel well might indeed be more inclined to pick up a new medium as a mood management strategy Second, we only investigated the broad, net effect of traditional media. We did not assess what content people engaged with or what their motivation for use was. Although we believe such net effects are important to investigate as first step, they may mask important interactions between content and user motivations 31 , 48 , Therefore, even though within-effects of traditional media are small, there may be meaningful under certain conditions Such an argument aligns with research which found noteworthy variation in the effect of social media Third, we looked at an intermediate time lag of one week, which might have missed the effect.

Therefore, to revise the answer from above: Under our assumptions of causality , the broad, net effect of traditional media during the week on well-being at the end of the week is likely too small to matter.

Besides the questions of causality and scope of media use, there are several limitations to our study. The self-reported estimates of time spent with a medium we relied on will be almost certainly a noisy measure of true media engagement 55 , In addition to that noise, the measures also reminded participants of their response in the previous week. That reminder might have reduced variance or introduced bias.

We call for more research directly measuring media use. Similarly, although they displayed decent psychometric properties, the well-being measures in the data set were not validated. The measure of affect in particular referred to affective well-being on the previous day, not the previous week. Although it allows a sensible test of the cumulative effect of media use during the week on well-being at the end of that week, the opposite direction is less plausible: Affect at the beginning of the week might not be strong enough to influence media use during the week that follows.

As a young man Rousseau had a relationship with an older, divorced woman, Mme. She does not ignore the fact that Rousseau had a longtime companion and common-law wife, Therese LeVasseur for most of his adult life, but the problem does not subside and resurfaces many times in his life with numerous affairs with other women which Cowls believes are all efforts to search out other mother substitutes, a pattern he could not help but to repeat over and over again.

The curious thing about the Cowles piece is that she goes about making her argument without explicitly stating what it is before she goes on to the gather evidence for her claim, but if we were going to look for an argument we are left to assume that her whole piece is an apology for Rousseau in which the bad choices or bad behavior he embarked upon was not his fault and he was the victim of a motherless childhood and so should not be blamed for any of his shortcomings.

In other words, she does not employ Dr. Freud or any other psychological experts very much to prove her point by offering any hard medical or scientific proof. Granted, it sounds like the kind of psychological explanation that we are used to hearing about in popular psychology, but the lack of quotes from experts in this field is apparent and goes a long way towards incredulity.

She does offer us a couple of lines from Pierre-Paul Clement, but this is nothing more that additional speculation. On balance it was a well written article that might even have some verity or certitude to it, but one cannot be sure without more documentary evidence from other experts.

What he is saying is that Rousseau does not like the city of Paris, the reason being that he met there some of his sharpest critics, but more to the point Rousseau abhorred city living and was in love with the country where he was closer to the natural beauty of unsoiled landscapes. The reason that this novel is new and unique is that the love —letter writer is a male writing to a female instead of the other way around, but more important than that he states that it is the first time a book of such letters was ever produced in this form Cornille, This is why Cornille thinks that Rousseau invented this genre.

The difference is that in Emile letters do not play any part in the education of Emile, which consists of a fictive couple, one the student the other the teacher who falls in love. According to Cornille, the love letter must be a declaration of love for the addressee stated in no uncertain terms. Along with this the recipient of the letter must feel the same way about the letter writer as he does about her.

Another element is that the couple must be far away from each other and missing each other at the same time. Last this implies that there is no other form of communication available to them.

Well, this might sound rather intuitive in the present, but this was in the mid-eighteenth century. Unless the writing of the letter is just a therapeutic exercise for the letter writer we might fail to see the point of this.

The fact that this is a male that is engaged in the expression of such feeling implies a gender role reversal and this is the essence of romantic literature. Admittedly this all sounds like madness and the reader of the novel cannot help but to feel sorry for this poor wretch.

On top of this when Julie receives the letter it does not have the intended effect. Not only does she see it as a threat, but it goes against the male code of behavior and is displeased that he wrote a letter to her like a women would. So now as if adding insult to injury the suffering lover must deal with his feelings of rejection as well as his agitated emotional state at being far away from the object of his desire. In John W. It appears that there is some general agreement that the protagonist in The New Eloise and the author have combined the fiction of the novel with the historical Rousseau.

Is appears that The New Eloise was very influential in the treatment of love affairs in novels after it was published and Kneller goes through a list of books that were influenced by Rousseau including Nerval and in fact the novel turns up in other novels as authors have their characters reading the Rousseau novel so it seems to have created a sensation at the time.

Just the fact that Rousseau was imitated so much by other authors is a lasting tribute to his creative talents. Rousseau, Kneller suggests was in the business of creating myths and legends about himself as well as fiction. So now we have Rousseau and his own double in his fiction, if indeed we accept it as such. In addition to this his enemies very much doubted his sincerity, particularly in his writings and unfortunately in the end Rousseau did not have any friends left at all, male or female because he seems to have driven then away with all kinds of wild accusations.

The truth to the matter is that Rousseau was not like any of his fictional characters and did not commit suicide or even attempt to do so; here properly lies the real different between the legend of Rousseau and the historical Rousseau. Cowles, Mary Jane. Project Muse. Kneller, John W.