I drank it!!!!

Dear optimist, pessimist, and realist,

While you were busy arguing about the glass of water, I drank it.

Sincerely,

The opportunist

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Tops of 2014: Social TV

 

If social media is the new water cooler, U.S. viewers certainly had their share of “let’s discuss” moments in 2014. From someone kind of getting devoured by an anaconda to the U.S. Men’s World Cup soccer squad trying to make a go of it to, well, zombies, there’s no shortage of Twitter activity during programs—and even in the days after.

This year, given the myriad social TV conversations taking place 24/7, Nielsen ranked the top series, special event telecasts and top sports events across Twitter. Nielsen also revealed the most-Tweeted-about minute in each category. After all, those OMG occasions often act as calls to action, prompting viewers to take to Twitter, and reminding fans who may have missed an episode to catch up in the days to come.

For the second year in a row, AMC had a show that topped our series list. The Walking Dead, in all its undead glory, had an average of nearly 5 million people seeing at least one Tweet about each new episode of the program. There was clearly a lot to talk about, as people sent an average of 576,000 Tweets about each episode.

2014 TOP 10 SERIES ON TWITTER

Rank Program Network Average Audience (000) Average Tweets (000)
1 The Walking Dead AMC 4,934 576
2 The Bachelor ABC 3,842 215
3 Pretty Little Liars ABC Family 3,807 489
4 American Horror Story: Freak Show FX 3,607 357
5 Game of Thrones HBO 3,507 159
6 Teen Wolf MTV 2,631 383
7 Scandal ABC 2,574 391
8 The Bachelorette ABC 2,410 104
9 The Voice NBC 2,063 236
10 Dancing With the Stars ABC 1,895 109
Source: Nielsen

The most-Tweeted TV series minute of 2014: The Voice (NBC), which garnered 310K Tweets at 8:59 p.m. EST on May 13, 2014.

2014 TOP 10 SPECIALS ON TWITTER

Rank Program Date Network Audience (000) Tweets (000)
1 The Oscars 03/02/14 ABC 13,924 11,163
2 The 56th Annual Grammy Awards 01/26/14 CBS 12,825 13,779
3 2014 MTV Video Music Awards 08/24/14 MTV 10,890 12,644
4 The 71st Annual Golden Globe Awards 01/12/14 NBC 10,437 2,359
5 2014 American Music Awards 11/23/14 ABC 10,265 5,651
6 2014 Billboard Music Awards 05/18/14 ABC 10,179 5,450
7 The BET Awards 2014 06/29/14 BET 9,302 10,891
8 2014 MTV Movie Awards 04/13/14 MTV 9,100 2,411
9 State of the Union 2014 01/28/14 TV Event 8,798 2,088
10 The 66th Primetime Emmy Awards 08/25/14 NBC 8,763 1,102
Source: Nielsen

The most-Tweeted special event minute of 2014: The Oscars (ABC), which garnered 203K Tweets at 10:07 p.m. EST on March 2, 2014.

2014 TOP 10 SPORTS EVENTS ON TWITTER

Rank Program Sports Event Date Network Audience (000) Tweets (000)
1 Super Bowl XLVIII Denver Broncos vs. Seattle Seahawks 02/02/14 FOX*, FOX Deportes 15,318 25,328
2 2014 FIFA World Cup Round of 16: Belgium vs. United States 07/01/14 ESPN*, ESPN Deportes, Univision, Univision Deportes 12,399 4,692
3 2014 FIFA World Cup Final: Germany vs. Argentina 07/13/14 ABC*, Univision, Univision Deportes 11,936 4,927
4 2014 FIFA World Cup Group G: United States vs. Germany 06/26/14 ESPN*, Univision, Univision Deportes 11,459 2,537
5 NFL Football NFC Championship: San Francisco 49ers at Seattle Seahawks 01/19/14 FOX*, FOX Deportes 11,383 4,957
6 2014 FIFA World Cup First Semifinal: Brazil vs. Germany 07/08/14 ESPN*, Univision, Univision Deportes 11,203 5,682
7 2014 FIFA World Cup Group G: Ghana vs. United States 06/16/14 ESPN*, ESPN Deportes, Univision, Univision Deportes 11,162 3,115
8 2014 FIFA World Cup Group G: United States vs. Portugal 06/22/14 ESPN*, ESPN Deportes, Univision, Univision Deportes 11,013 3,629
9 NFL Football AFC Championship: New England Patriots at Denver Broncos 01/19/14 CBS 10,863 2,492
10 2014 Vizio BCS National Championship Auburn vs. Florida State 01/06/14 ESPN*, ESPN Deportes 10,404 4,392
Source: Nielsen

The most-Tweeted sports event minute of 2014: Super Bowl XLVIII (FOX), which garnered 301K Tweets at 10:00 p.m. EST on Feb. 2, 2014.

METHODOLOGY

Source: Nielsen. Data from 1/1/2014-11/30/2014. Nielsen Social captures relevant Tweets in the U.S. from three hours before through three hours after broadcast, local time.  Unique Audience  measures the audience of relevant Tweets ascribed to a program from when the Tweets are sent until the end of the broadcast day at 5am. Sports Events, Series, and Specials include those on Broadcast and National Cable Networks only. Sports Events and Specials are across all day parts and are ranked by Unique Audience for each individual telecast. Series include new/live primetime and late fringe programming only and are ranked by Average Unique Audience across New/Live episodes during the time period. For multicast Sports Events, networks are listed alphabetically and metrics reflect the highest Unique Audience across all airing networks, denoted with an asterisk. Data does not include airings from 6/13/14-6/15/14; reach metrics are unavailable for those dates.

La discrimination sur Internet

Depuis des années, dans mes articles et émissions de télévision, j’ai utilisé le nom de Netizen. Netizen signifie citoyen d’Internet. Ce nom n’est pas seulement valable en Turquie mais partout dans le monde, il désigne la même chose.
Internet est un cyber ensemble et ceux qui y vivent sont des adhérents à une communauté virtuelle.
Cette communauté est composée de différents groupes comme Facebook dont la population est plus grande que celle de la Chine. Comme les pays, ces groupes sont liés les uns aux autres par des sentiments définis.
Vous pouvez voir que cette idée n’appartient pas qu’à moi en faisant juste une recherche de la carte mondiale d’Internet sur Google.
S’il existe un tel ensemble, par exemple, les utilisateurs d’Apple étaient une partie de cette communauté, Apple aura-t-il le droit d’avoir un comportement différent selon leur langue, leur religion et leur race ? Ce qu’il fera là, serait de la discrimination ?
Il y a quelques années de cela, j’ai tenté d’acheter un produit en me connectant sur le site Internet de Tiffany Co. J’ai constaté que certains prix étaient fermés parce que j’étais en Turquie. Quand j’ai pris contact avec eux pour expliquer que j’étais en Turquie et que je ne voyais pas certains prix, ils m’ont alors donné raison et ont présenté leurs excuses. La raison évoquée était la variation des frais liés au taux de change, aux franchises, et à la logistique.

Aujourd’hui, avant d’écrire mon article, je me suis à nouveau connecté au site et ai vu que les prix étaient accessibles.
La variation des prix est une chose compréhensible mais ne pas donner accès à ces prix est une discrimination. Personne n’a le droit de faire ça.

Par exemple, les recherches sur Google sont propres à la personne, l’information de la localisation peut être donnée selon le souhait mais l’information communiquée suite à la recherche est identique pour tout le monde.

Jusqu’à maintenant, je n’ai pas connaissance de personne ayant été lésée par Google dans ses recherches pour cette raison.

Le service de Facebook est identique pour tout le monde. Il ne contient pas de discrimination. Quand je vois les vécus de mes clients dont le compte a été piraté, Facebook est également très performant en Turquie en termes de support. Bien sûr je dois citer le sérieux travail de l’ancien Directeur Général de Microsoft Turquie M. Caglayan Arkan et de son avocat M. Yasin Beceni derrière cette performance.

Mais de toute manière, au niveau international, Facebook a déjà prouvé son excellence à ce sujet.

En revanche, il n’est pas possible de dire la même chose pour Apple. Des magasins d’application, Apple Store, séparées sur la base de la localisation proposent des services différents à tout le monde. Même sans aucune action sur la localisation, le fait que certaines applications ne fonctionnent pas en Turquie est la raison apparente de cela.
Supposer que tous les citoyens d’Internet sont égaux et avoir un esprit de support et d’application basé sur la localisation est la preuve apparente que la discrimination se fait sur la langue, la religion et la race. Ce qui est encore plus triste est que les acheteurs ayant réalisé leurs achats dans 2 magasins différents Apple Store n’aient pas l’autorisation de partager leurs applications via la fonction « famille » d’ios8. Apple Store a distingué les citoyens d’Internet selon leur langue, leur religion et leur race.

Je ne ressens même pas le besoin d’évoquer Twitter, parce que l’origine de leur discrimination est leur manque de réussite dans les services clients et leur désorganisation. Attendre d’eux qu’ils aient une approche de réaliser cette discrimination est pour le moment insensé. Les Turcs ont une belle expression pour traduire ceci : « Twitter doit encore manger 40 fours de pain avant d’y parvenir »

Discrimination on the Internet

Apple stop discriminationFor years in my articles and television programs, I used the name of Netizen. Netizen means a citizen of the Internet. This name is not only valid in Turkey but all over the world, it means the same thing.Internet is a cyber together and those who live there are participants in a virtual community.

This community is composed of different groups like Facebook with a population larger than that of China. Since countries, such groups are bonded to each other by definite feelings.You can see that this idea does not belong to me by just doing a search of the Internet world map on Google.

If there is such a set, for example, Apple users were a part of this community, Apple Will he have the right to have a different behavior depending on their language, religion and race? What will there be discrimination?

There are a few years back, I tried to buy a product by connecting me to the website of Tiffany Co. I have found that some prices were closed because I was in Turkey. When I contacted them to explain that I was in Turkey and I do not see some prices, they then gave me reason and apologized. The reason given was the change in costs associated with the exchange rates, deductibles, and logistics.

Today, before writing my article, I once again connected to the site and saw that prices were accessible.The price change is an understandable thing but do not provide access to such price discrimination. Nobody has the right to do that.

For example, Google searches are specific to the person, the location information can be given as desired, but the information provided after the search is the same for everyone.So far I am not aware of anyone having been injured by Google in its research for this reason.

The service Facebook is identical for everyone. It contains no discrimination. When I see the experiences of my clients whose account was hacked, Facebook is also very powerful in Turkey in terms of support. Of course I have to mention the serious work of the former General Manager of Microsoft Turkey Caglayan Arkan and his lawyer Mr. Yasin Beceni behind this performance.

But in any event, at international level, Facebook has already proven its excellence about it. However, it is not possible to say the same thing for Apple. Application stores, Apple Store, separated on the basis of location offer different services to everyone. Even without any action on the location, the fact that some applications do not work in Turkey is the apparent reason for this.

Assume that all citizens are equal and the Internet have a spirit of support and application based on location is the apparent evidence that discrimination is on language, religion and race. What is even sadder is that buyers who have produced their purchases in 2 different stores Apple Store did not have permission to share their applications via the “family” of ios8 function. Apple Store has distinguished citizens of the Internet by language, religion and race.

I do not even feel the need to mention Twitter, because the source of their discrimination is their lack of success in customer service and disorganization. Expect them to have an approach to achieve this discrimination is the senseless moment. The Turks have a beautiful expression to translate this: “Twitter should still eat 40 bread ovens before achieved”

Social media studies are misleading, according to study

Social media has revolutionized the behavioral sciences. Now, social scientists can use individuals’ social networks to gather large amounts of data, which can then be mined to uncover how groups of individuals think or behave.

According to a press release from McGill University, “A growing number of academic researchers are mining social media data to learn about both online and offline human behavior. In recent years, studies have claimed the ability to predict everything from summer blockbusters to fluctuations in the stock market.”

However, two computer scientists, Juergen Pfeffer and Derek Ruths at McGill University and Carnegie Mellon University respectively, have recently published an article in the journal Science warning that these datasets may be misleading researchers. The scientists write that there are biases inherent to gathering information on various social media platforms, and these shortcomings must be corrected or acknowledged when publishing studies using this data.

As Pfeffer tells Phys.org, “Not everything that can be labeled as ‘Big Data’ is automatically great…But the old adage of behavioral research still applies: Know Your Data.” Still, Pfeffer acknowledges that the attraction of using this data, however flawed, can be very strong. He continues, “People want to say something about what’s happening in the world and social media is a quick way to tap into that…You get the behavior of millions of people—for free.”

Still, Pfeffer and Ruths directly address many of the challenges of interpreting this data in their article. For example, different social media platforms (i.e. Pinterest vs. Facebook) attract different users. For example, Pinterest has mostly female users aged 25-34, thus making generalizations about human behavior from data collected from this platform is likely to lead to biased results.

There are a number of other serious challenges when interpreting social media datasets. For example, as described in the McGill press release, “Large numbers of spammers and bots, which masquerade as normal users on social media, get mistakenly incorporated into many measurements and predictions of human behavior.” As well, “Researchers often report results for groups of easy-to-classify users, topics and events, making new methods seem more accurate than they actually are. For instance, efforts to infer political orientation of Twitter users achieve barely 65% accuracy for typical users—even though studies (focusing on politically active users) have claimed 90% accuracy.”

These challenges and shortcomings are not limited to interpreting social media data, but are well known in other fields such as statistics and epidemiology, among other fields. As Ruths tells Chris Chipello of the McGill newsroom, “The common thread in all these issues is the need for researchers to be more acutely aware of what they’re actually analyzing when working with social media data.”