compte netflix gratuit Have you seen every possible and unimaginable series on Netflix? Are you just disappointed and think it’s time to unsubscribe?
Whatever your type of subscription to the Netflix platform, know that it is easy to delete your account.
In this tutorial, we explain how to cancel your Netflix subscription, whether you still have the welcome offer or not.
Unsubscribe from Netflix
Netflix is an online video platform that offers three types of subscriptions ranging from € 7.99 to € 15.99.
If for any reason you wish to end your subscription then follow these video streaming service unsubscribe steps.
- Sign into your account.
- Click on your profile at the top right and select Account .
- In the Subscription and Billing section , click on the Cancel subscription option .
- On the page that opens, all you have to do is click on Complete the cancellation .
- Your cancellation is now registered and will take effect on the last day of the month.Please note that you can reactivate your account at any time. The latter will be permanently closed 10 months after deactivation.If you consider this delay too long, then Netflix advises you to send an email to firstname.lastname@example.org , from the email address given during your registration.Also, we recommend that you delete your bank details, in order to avoid any use of your account without your consent. You can also request it in your cancellation email.Remove a profile from your Netflix accountIf you only want to delete one or more profiles associated with your account, then follow the steps below.
Log in to Netflix.
Click on your profile and select Account .
In the My Profile section , click the Manage Profiles option on the right.
Choose the profile, then click Remove.
For more information on boosting and saving your personal data, then go to the help center.
To access it, click Account , then click Help Center from the drop-down list. Finally, in the search bar, type Information deletion and information retention policy .
Microsoft Advertising has given its users access to high-quality images with their new Shuttershock partnership. Here’s how you can make the most of it.
Read more at PPCHero.com
I came across an interesting Search Engine Land post last week. It inspired me to search and see if I could find a related patent from Google:
I tried reproducing search suggestions shown to the author of the Search Engine Land article, but Google would not return those. Google may be experimenting with a limited number of searchers instead of showing those results to all searchers. I did find a patent about similar search suggestions.
When Google shows search suggestions on something you may have looked for in the past, that predicted query suggestion is likely related to a patent I’ve written about before, Autocompletion using previously submitted query data.
I wrote about an update in a continuation patent, but did not provide many details about how it works: How Google Predicts Autocomplete Query Suggestions is Updated.
Some interesting parts on identifying search suggestions and ranking them inspired me to write this post.
Search Suggestions Based on Previously Submitted Query Data
This patent is about: “using previously submitted query data to anticipate a user’s search request.”
Google has a long memory, and it remembers a lot about what someone might search for.
The description includes many assumptions that search engineers make about searchers (often an interesting reason to read through patents). Here are some from this patent that is worth thinking about:
Internet search engines aim to identify documents or other items that are relevant to a user’s needs and to present the documents or items in a manner that is most useful to the user. Such activity often involves a fair amount of mind-reading–inferring from various clues what the user wants. Certain clues may be user-specific. For example, the knowledge that a user is requesting a mobile device, and knowledge of the location of the device, can result in much better search results for such a user.
Clues about a user’s needs may also be more general. For example, search results can have elevated importance, or inferred relevance, if several other search results link to them. If the linking results are themselves highly relevant, then the linked-to results may have particularly high relevance. Such an approach to determining relevance may be premised on the assumption that, if authors of web pages felt that another web site was relevant enough to be linked to, then web searchers would also find the site to be particularly relevant. In short, the web authors “vote up” the relevance of the sites.
Other various inputs may be used instead of, or in addition to, such techniques for determining and ranking search results. For example, user reactions to particular search results or search result lists may be gauged, so that results on which users often click will receive a higher ranking. The general assumption under such an approach is that searching users are often the best judges of relevance, so that if they select a particular search result, it is likely to be relevant, or at least more relevant than the presented alternatives.
A Summary of the Search Suggestions Process Based on Previous Submitted Queries
The Description for this patent begins with a summary of the process in the patent. A “Detailed Description” is about how search at Google works, and what powers this search suggestion process.
Search suggestions may be based on user queries searched for before.
In the summary section of the patent, we are told about how the patent may address some assumptions:
When anticipating user search requests, responding involves certain methods for processing query information. Those include:
- Receiving query information at a server system, with a part of a query from a searcher
- Obtaining a set of predicted queries relevant to the part of the searcher’s query based on query and data indicative of the searcher relative to before submitted queries
- Providing the set of predicted queries to the searcher
The patent also points out more features involved in the process such as obtaining the predicted queries including ordering the set of predicted queries based upon ranking criteria.
Those ranking criteria based upon the data indicative of searcher’s behavior relative to previously submitted queries.
Data about the searcher’s behavior about those previously submitted queries may include:
- Click data
- Location-specific data
- Language-specific data
- Other similar types of data
The patent points out the following as advantages of following the process described in the patent:
A search assistant receives query information from a search requestor before a searcher completely inputting the query.
Information associated with previous user (or users) searches (such as click data associated with search results) is collected. From the query information and the previous search information, a set of predicted queries is produced and provided to the search requestor for presentation.
The patent can be found at:
Autocompletion using previously submitted query data
Inventors: Michael Herscovici, Dan Guez, and Hyung-Jin Kim
Assignee: Google Inc.
US Patent: 9,740,780
Granted: August 22, 2017
Filed: December 1, 2014
A computer-implemented method for processing query information includes receiving query information at a server system. The query information includes a portion of a query from a search requestor. The method also includes obtaining a set of predicted queries relevant to the portion of the search requestor query based upon the portion of the query from the search requestor and data indicative of search requestor behavior relative to previously submitted queries. The method also includes providing the set of predicted queries to the search requestor.
Analysis of Ranking and Selection of Search Suggestions Based Upon Previous Query Data
The “Detailed Description” section of this search suggestions patent provides some insightful analysis about search at Google.
Relevance and Backlinks and a Rank Modifying Engine Lead to Ranking For Many Results at Google
This patent points out some of how search works at Google. It tells us that:
- The purpose of the patent is to “improve the relevance of results obtained from submitting search queries.”
- It describes ranking documents for a query as something that can be “performed using traditional techniques for determining an information retrieval (IR) score for indexed documents because of a given query.” And the relevance of a particular document about a query term may use look at the general level of back-links to a document containing matches for a search term to infer a document’s relevance. As the patent tells us:
In particular, if a document is linked to (e.g., is the target of a hyperlink) by many other relevant documents (e.g., documents that also contain matches for the search terms), it can be inferred that the target document is particularly relevant. This inference can be made because the authors of the pointing documents presumably point, for the most part, to other documents that are relevant to their audience.
- We are given more details about some results being even more relevant than ones with backlinks. We are told that:
If the pointing documents are in turn the targets of links from other relevant documents, they can be considered more relevant, and the first document can be considered particularly relevant because it is the target of relevant (or even highly relevant) documents. Such a technique may be the determinant of a document’s relevance or one o multiple determinants. The technique is exemplified in some systems that treat a link from one web page to another as an indication of quality for the latter page so that the page with the most such quality indicators is rated higher than others. Appropriate techniques can also be used to identify and eliminate attempts to cast false votes to artificially drive up the relevance of a page.
- There is another step that could potentially make some results even more relevant that involve what is referred to as a rank modifier engine:
To further improve such traditional document ranking techniques, the ranking engine can receive an additional signal from a rank modifier engine to assist in determining an appropriate ranking for the documents. The rank modifier engine provides one or more prior models, or one or more measures of relevance for the documents based on one or more prior models, which can be used by the ranking engine to improve the search results’ ranking provided to the user. In general, a prior model represents a background probability of document result selection given the values of multiple selected features, as described further below. The rank modifier engine can perform one or more of the operations described below to generate the one or more prior models, or the one or more measures of relevance based on one or more prior models.
This is a more detailed description of ranking than we normally see at Google. The section above references a Rank Modifier Engine that will be described in more detail further down this post
Indexing, Scoring, Ranking, and Rank Modifier Engine
The information retrieval system from this patent includes many different components:
- Indexing engine
- Scoring engine
- Ranking engine
- Rank modifier engine
A scoring engine may provide scores for document results based on many different features including:
- Content-based features that link a query to document results
- query-independent features that generally state the quality of document results
Content-based features include aspects of document format, such as query matches to a title or anchor text in an HTML (HyperText Markup Language) page.
The query-independent features can include aspects of document cross-referencing, such as a rank of the document or the domain.
Moreover, the particular functions used by the scoring engine can be tuned, adjust the various feature contributions to the final IR score, using automatic or semi-automatic processes.
A ranking engine can produce a ranking of document search results for display to a searcher based on IR scores received from the scoring engine and possibly one or more signals from the rank modifier engine.
Logged selection information could capture for each selection:
- the query (Q)
- the document (D)
- the time (T) on the document
- the language (L) employed by the user
- the country (C) where the user is likely located (e.g., based on the server used to access the IR system).
Recorded information about a searcher’s interactions with presented rankings:
- Negative information, such as presented document results that were not clicked on
- Position(s) of click(s) in the user interface
- IR scores of clicked results
- IR scores of all results shown before the clicked result
- Titles and snippets shown to the user before the clicked result
- The user’s cookie
- Cookie age
- IP (Internet Protocol) address
- User agent of the browser
More recorded information (as described in this post below) about building a prior model.
Rank Modifier Engine
Similar recorded information (e.g., IR scores, position, etc.) for an entire session, or many sessions, including every click that occurs both before and after a current click.
Stored Information in the result selection logs used by the rank modifier engine to generate one or more signals to the ranking engine.
The stored information in the search results selection logs along with the information collected by the tracking component may also be accessible by a search assistant, which is also a component of the information retrieval system.
Along with receiving information from these components, the search assistant could also monitor a user’s entry of a search query.
On receiving a partial search query, the query along with the information (e.g., click data) from the tracking component and the results selection log(s) may be used to predict a searcher’s contemplated complete query.
Based on this information, predictions may be ordered according to one or more ranking criteria before being presented to assist the user in completing the query.
Presentation of a Search Suggestion
As a searcher enters a search query, the searcher’s input is monitored.
Before a searcher signals they have completed entering the search query, a part of the query goes to the search engine.
Also, data such as click data (or other types of previously collected information) may is sent with the query portion.
The part of the query sent may be:
- A few characters
- A search term
- More than one search term
- Any other combination of characters and terms
The search engine receives the partial query and the data (e.g., click data) for processing and makes predictions) about the searcher’s contemplated complete query.
Relevant information may be retrieved for processing with the received partial query to produce search suggestions predictions.
Predictions may be ordered according to one or more ranking criteria.
So, queries that have been submitted at a higher frequency may be ordered before queries submitted at lower frequencies.
The search engine may also use various types of information for ranking and ordering predicted queries as search suggestions.
Information about previously entered search queries may be used to make ordered predictions.
Previous queries may include search queries associated with the same user, another user, or from a community of users.
If one of the predicted queries is what the searcher intended as the desired query, the searcher may select that predicted query and proceed without having to finish entering the desired query.
Or, if the predicted queries do not reflect what the searcher had in mind, then the searcher can continue entering the desired search query, which could trigger one or more other sets of search suggestions.
Ranking User Submitted Previous Queries as Search Suggestions
A few different processes may rank and order predicted search queries:
- Ordered predicted search queries following frequency of submission by a community of users
- Using time constraints with search queries ordered under the last time/date value of the query
- Using personalization information or community information about subjects, concepts or categories of information of interest to the searcher (from prior search or browsing information)
- Personalization from an associated group of the searcher or belonging to (a member or an employee.)
- According to first ranking criteria, such as predefined popularity criteria, and then possibly reordered if any of the predicted search queries match the user personalization information of the user, to place the matching predicted search queries at or closer to the top of the ordered set of predicted search queries
- Using Information provided by the tracking component and the result selection log(s) for ranking and ordering the predicted search queries. (click data, language-specific, and country-specific data.)
- Using processed click data (e.g., aggregated click data for a given query) for ranking and ordering predicted search queries – or each query a score may be calculated by summing click data (e.g., weighted clicks, etc.) on documents associated with the query, and predicted queries may be ordered based upon the score (e.g., higher values representing better)
An Information Model Based On Earlier Submitted Query Data to Obtain Search Suggestions Predictions
This model can predict query data that may satisfy a searcher the most by looking at long click information. A timer can track how long a user views or “dwells” on a document.
That amount of time is “click data”.
More time dwelling on a document is a “long click”, indicating a user found the document to be relevant for their query.
A brief period viewing a document is a “short click”, interpreted as a lack of document relevance.
Click data is a count of each click type (e.g., long, medium, short) for a particular query and document combination.
This click data from model queries for a given document can create a quality of result statistic for that document to enhance a ranking of a document.
Quality of result statistic can be a weighted average of the count of long clicks for a given document and query.
This description from the patent tells us about how click data might be stored in tuples:
A search engine (e.g., the search engine) or other processes may create a record in the model for documents that are selected by users in response to a query or a partial query. Each record within the model (herein referred to as a tuple:
) is at least a combination of a query submitted by users, a document reference selected by users in response to that query, and aggregation of click data for all users that select the document reference in response to the query. The aggregate click data can be viewed as an indication of document relevance. In various implementations, model data can be location-specific (e.g. country, state, etc) or language-specific. For example, a country-specific tuple would include the country from where the user query originated from in whereas a language-specific tuple would include the language of the user query. Other extensions of model data are possible.
The model may also include Post-click behavior tracked by the tracking component.
This patent includes information about how Google may use click tracking data when ranking search suggestion predictions. It tells us about sollected data about clicks:
The information gathered for each click can include:
(1) the query (Q) the user entered,
(2) the document result (D) the user clicked on,
(3) the time (T) on the document,
(4) the interface language (L) (which can be given by the user),
(5) the country (C) of the user (identified by the host that they use, such as www-store-co-uk to sho the United Kingdom), and
(6) more aspects of the user and session.
Time (T) can be measured as the time between the initial click through to the document result until the time the user comes back to the main page and clicks on another document result.
An assessment about the time (T) and whether it indicates a longer view of the document result or a shorter view of the document result (since longer views are generally indicative of quality for the click through the result.) This assessment about the time (T) can further be made in conjunction with various weighting techniques.
Beyond Long Clicks
Document views from the selections can be weighted based on viewing length information to produce weighted views of the document result.
So, rather than distinguishing long clicks from short clicks, a wider range of click through viewing times can be included in the assessment of result quality, where longer viewing times in the range are given more weight than shorter viewing times.
Predicted Search Suggestions
Google will sometimes display search suggestions using autocomplete and also based upon user data from previous queries from a searcher’s previous search history. Or from the history of someone whom the searcher may be associated with, such as a fellow member of an organization or a co-worker.
While results related to those previous queries can be ranked based upon relevance and backlinks, the search suggestions may include results that searchers spent long clicks upon, including long times viewing.
So under this patent, predictions about search suggestions chosen using autocomplete may best meet a searcher’s informational needs by being searches that include results remembered as resulting in long clicks and long viewing times.
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“Based on guidance from health and government experts, as well as decisions drawn from our internal discussions about these matters, we are allowing employees to continue voluntarily working from home until July 2021,” a spokeswoman told the Reuters news agency.
Facebook also said it will provide employees with an additional $ 1,000 to spend on “home office needs.”
Late last month Google also extended its coronavirus remote work provision, saying staff would be able to continue working from home until the end of June 2021.
Both tech giants have major office presences in a number of cities around the world. And despite the pandemic forcing them into offering more flexible working arrangements than they usually do, the pair have continued to build out their physical office footprints, signaling a commitment to operating their own workplaces. (Perhaps unsurprisingly, given how much money they’ve ploughed in over the years to turn offices into perk-filled playgrounds designed to keep staff on site for longer — with benefits such as free snacks and meals, nap pods, video games arcade rooms and even health centers.)
Earlier this month, Facebook secured the main office lease on an iconic building in New York, for example — adding 730,000 square feet to its existing 2.2 million square feet of office space. Google has continued to push ahead with a flagship development in the U.K. capital’s King’s Cross area, with work resuming last month on the site for its planned London “landscraper” HQ.
In late July, Apple said staff won’t return to offices until at least early 2021 — cautioning that any return to physical offices would depend on whether an effective vaccine and/or successful therapeutics are available. So the iPhone maker looks prepared for a home-working coronavirus long haul.
As questions swirl over the future of the physical office now that human contact is itself a public health risk, the deepest pocketed tech giants are paradoxically showing they’re not willing to abandon the traditional workplace altogether and go all in on modern technologies that allow office work to be done remotely.
Whether remote work played any role in the company’s recent account breach is one open question. It has said phone spear phishing was used to trick staff to gain network access credentials.
Certainly, security concerns have been generally raised about the risk of more staff working remotely during the pandemic — where they may be outside a corporate firewall and more vulnerable to attackers.
A Facebook spokeswoman did not respond when we asked whether the company will offer its own staff the option to work remotely permanently. But the company does not appear prepared to go so far — not least judging by signing new leases on massive office spaces.
Facebook has been retooling its approach to physical offices in the wake of the COVID-19 pandemic, announcing in May it would be setting up new company hubs in Denver, Dallas and Atlanta.
It also said it would focus on finding new hires in areas near its existing offices — including in cities such as San Diego, Portland, Philadelphia and Pittsburgh.
Facebook CEO Mark Zuckerberg said then that over the course of the next decade half of the company could be working fully remotely. Though he said certain kinds of roles would not be eligible for all-remote work — such as those doing work in divisions like hardware development, data centers, recruiting, policy and partnerships.
- Companies can rank for trending keywords by combining content marketing with current events.
- There are some specific Dos and Don’ts for creating this content in a tasteful manner.
- Dos include questioning your motives, thinking of clients first, keeping content value-driven, and giving company updates.
- Don’ts include pretending nothing is going on, posting irrelevant content, abandoning your existing SEO strategy, or giving up.
- VP of sales and marketing at Strategic Sales & Marketing, helps you achieve SEO value while maintaining sensitivity using trending keywords.
A good content marketing strategy should already be backed up by a list of target keywords or keyphrases your business is trying to rank for. But alongside these evergreen keywords, incorporating trending search terms into content marketing can boost SEO significantly. There’s already plenty of advice for finding trending keywords, but how do we harness their power without being distasteful?
Approaching serious current events in content marketing can be a tricky wire to walk. In 2020 alone, businesses and marketing teams everywhere have struggled to decide how to use keywords related to the COVID-19 crisis, the Black Lives Matter movement, Brexit, increasing climate change, and even a sighting of murder hornets. To avoid embarrassment and truly rank for important trending searches in an authentic way, follow these dos and don’ts.
Do: Question your motives
A national or global news story breaks, new keywords start trending immediately, and the first thing you think is…
If the answer was “Ooo I can use this”, then you may not have the best motives for adding that current event to your content marketing. Stopping to question your motives is the first step to harnessing the power of trending keywords without making a marketing blunder. It should and will take deep thought as to how to approach a trending topic with sensitivity.
Ranking for trending keywords shouldn’t be just about good SEO. Your keyword usage serves as a connection between what is important to both a brand and its consumers. When the great toilet paper shortage of 2020 occurred, bath tissue companies could have easily changed their marketing to fuel the need and push profits even more. But brands like Cottonelle took the exact opposite approach with their #ShareASquare social media campaign and partnership with United Way. Content marketing should always be motivated first and foremost by your business values, not your bottom line.
Don’t: Pretend nothing is going on
Some companies read the news and move right along with business as usual. That’s okay if you don’t have the right motives or anything significant to add value for your audience. However, the conversation surrounding authentic branding is growing, and more and more consumers are wanting to see companies respond to important events with transparency and empathy.
In a 2019 Deloitte study, 55% of survey respondents reported believing that “businesses today have a greater responsibility to act on issues related to their purpose”. It’s okay to ignore which Kardashian is getting divorced when it comes to your marketing. But issues like climate change, world health, and racism cannot be ignored or you risk alienating consumers who equate silence with complicity.
Do: Think of your clients first
Any good company already has their customers at the center of their content marketing strategy. Now more than ever, businesses need to refocus their marketing and make sure they are putting their customers’ needs first. This can be difficult in a climate where world events are creating new and different needs seemingly daily.
Consumers are shifting their needs and preferences to new types of content and new ways of engaging with companies. In particular, educational content is gaining popularity and driving “how to” searches. Think of what your clients need to know or hear in order to interact with your business, products, or services. The client always comes first.
Don’t: Provide irrelevant content
Anything you share concerning current events needs to be connected to your business in some way or another. Posting something completely irrelevant or out of the blue may throw off and leave a sour taste with customers and followers. If you can’t tie the content directly to your customer’s needs, then it’s likely not relevant enough to share.
One way to connect your business with seeming-distant trending topics is to think of secondary trending searches still related to your industry or product. COVID-19 has changed the way people live which has led to a wide variety of spiking trends such as gardening or home haircuts. There’s always an authentic way to connect a current event to your company.
Do: Keep your content marketing value-driven
Even if you’re making a commentary or stating a position or opinion, you still need to add value to your content. Every message should have a takeaway that readers can apply to better themselves or their lives. Sometimes the value is in buying your service or product, but other times the value lies in the emotional connection imparted to the reader.
Think, what does value mean to your clients right now? Nike is a great example of a company providing new value to consumers. With gyms everywhere shutting down, Nike released their workout content for free and ramped up posting blogs to its apps and website. Their latest trend-focused content features celebrities challenging at-home exercisers to various workouts. Creating this value-driven content allows them to rank for many trending 2020 searches such as “at-home workout” as well as various trending athletes and celebrities.
Source: Google Trends
Don’t: Abandon your content marketing strategy
In turbulent times, your audience needs some nuggets of normalcy. A good content marketing strategy will provide the flexibility to adapt to sudden world changes or important events that need commenting on without abandoning the original plan. That being said, you’ll probably need to pivot on a few things, or at least give your audience a heads up about why they may still be seeing the content you already had planned.
Following travel restrictions due to Covid-19, Travel Zoo issued an email and blog statement explaining why they were going to continue on with their email series promoting travel, even when they knew their audience wouldn’t need their services right then. They add that they will be offering the same great content and deals they had planned, so email subscribers will “continue to find experiences that inspire and enlighten, whether in fantastic locations around the world or through something new you can try right in your home”.
Abandoning evergreen keywords for trending ones can lead to a big drop in your overall SEO. Remember, these searches are “trending” for a reason. That means, just as quickly as consumers are finding your recent content marketing, they are moving on to new trends and keywords.
Do: Give company updates
Once you decide to approach a trending topic in a blog, email, or any piece of content, it’s good to give clients company updates related to your first statement. This creates more opportunities for using related trending searches without keyword-stuffing your original content. This also shows consumers that you follow through on your promises which builds customer–brand rapport.
A great example of a constant commitment to this is Ben & Jerry’s Issues We Care About blog. These articles keep consumers interested in the company while ranking their content high in trending search results.
Don’t: Give up
Using trending keywords related to current events is key to helping consumers find your content. Just because it may take more consideration to create does not mean it’s worth skipping. “Going dark” can hurt exposure, engagement, and sales. And even businesses that weather the storm will face further recovery time if their company was out of mind due to lack of marketing.
Times are tough, there’s no doubt about it. But when it comes to keeping your business running in the face of global catastrophe, you cannot give up, especially on your marketing. Rather, content marketing and reaching clients and consumers at home requires your doubled commitment. You can make your content a place people turn to for wisdom and perspective—all while scoring those trending keyword SEO points.
Gregg Schwartz is the VP of sales and marketing at Strategic Sales & Marketing, a lead-generation firm based in Connecticut.
The post How to use trending keywords from current events in content marketing appeared first on Search Engine Watch.
Though the Facebook-owned app doesn’t give users complete control, there are ways to limit the data it collects and the types of ads you see.
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Beta Technologies’ Alia, which debuted Friday, draws inspiration from the ultra-efficient Arctic tern. The craft may one day transport organs for transplants.
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Alexis Ohanian, the founder and former CEO of Reddit, stepped down from his position on the company’s board Friday as the U.S. roils with nationwide protests against police brutality after Minneapolis police killed George Floyd, an unarmed black man.
Ohanian is calling on the company he founded to fill his position with a black board member, a high-profile step for a company with its own rocky track record around issues of race.
“I believe resignation can actually be an act of leadership from people in power right now,” Ohanian said in his announcement. “To everyone fighting to fix our broken nation: do not stop.”
I've resigned as a member of the reddit board, I have urged them to fill my seat with a black candidate, + I will use future gains on my Reddit stock to serve the black community, chiefly to curb racial hate, and I’m starting with a pledge of $ 1M to @kaepernick7’s @yourrightscamp
— Alexis Ohanian Sr. (@alexisohanian) June 5, 2020
With the decision, Ohanian also announced that future gains of his company stock would be invested in the black community, “chiefly to curb racial hate.” That amount could total to around $ 50 million, according to reliable sources. His first move will be to give $ 1 million to Know Your Rights Camp, an organization founded by Colin Kaepernick that focuses on self-empowerment and safety for black and brown communities.
Many leaders within tech are calling for the industry to have its own reckoning with entrenched racism, an effort Ohanian’s move may amplify. Tech companies have long been criticized for their broad lack of black leadership at the highest levels, a failing that likely factors into their myriad policy failures around race — like the fact that Facebook only banned white nationalism one year ago.
“I co-founded @reddit 15 years ago to help people find community and a sense of belonging. It is long overdue to do the right thing. I’m doing this for me, for my family, and for my country” Ohanian wrote on Twitter. “I’m saying this as a father who needs to be able to answer his black daughter when she asks: ‘What did you do?’ ”
Update: Reddit CEO Steve Huffman (u/spez) said that the company would honor the request to bring on a black board member in Ohanian’s place.
Ohanian stepped away from his daily duties at Reddit in 2018 but kept a seat on the board at the time. His transition to being more hands-off at the company he founded has been gradual over the last few years as he spent more time on Initialized Capital, an early-stage venture fund he co-founded. In recent years, Ohanian has also become a more outspoken advocate for policies like paid family leave, calling for more equitable, flexible leave policies and citing his own experience as a father. In 2017, Ohanian had a daughter with his wife, tennis legend Serena Williams.
Reddit occupies a unique place among social media platforms. It has largely avoided the spotlight of platforms like Facebook and Twitter, but not for lack of its own systemic problems. Though it hasn’t been as high-profile, the platform has faced its own reckoning around harmful content in recent years for hosting virulently racist content on subcommunities like r/blackpeoplehate, r/The_Donald and others. Reddit has taken action against those communities over time, either banning them outright or placing them in a state of “quarantine” where they are not surfaced in search or recommendations and require a user to click through to view them.
The company’s history with diversifying its leadership has been spotty. In 2015, internal turmoil at the company and a backlash from its users led to the resignation of the company’s interim CEO, Ellen Pao. As we reported in 2016, more than a dozen senior Reddit employees, many of them women and people of color, left the company in the resulting tumult. As it continued its overdue campaign to crack down on violence and hate speech, Reddit brought in its first female board member, Porter Gale, last year.
In a post on Reddit, Huffman also addressed the company’s troubled history of allowing often violent and extreme racist content to flourish on the platform.
“In 2018, I confusingly said racism is not against the rules, but also isn’t welcome on Reddit. This gap between our content policy and our values has eroded our effectiveness in combating hate and racism on Reddit; I accept full responsibility for this,” Huffman said.
He also acknowledged concerns from employees about the company’s policy decisions, expressed this week in response to an email he sent out about ongoing protests and the killing of George Floyd.
“These questions, which I know are coming from a place of real pain and which I take to heart, are really a statement: There is an unacceptable gap between our beliefs as people and a company, and what you see in our content policy,” Huffman said.
Modern apps and services are a mixed bag when it comes to accessibility, and people with conditions that prevent them from using the usual smartphone or mouse and keyboard don’t often have good alternatives. Eye-tracking tech leader Tobii has engineered a solution with a set of popular apps that are built for navigation through gaze alone.
Working with a third-party developer that specializes in accessibility development, the company’s new suite of apps includes: Facebook, FB Messenger, WhatsApp, Instagram, Google, Google Calendar, Google Translate, Netflix, Spotify, YouTube, MSN and Android Messages.
These custom apps are for Tobii’s eye-tracking I-Series tablets or Windows PCs using Tobii peripherals and software.
Previously, users would generally have to use the generic web interfaces for those services, or some kind of extra layer on top of the native apps. It can work, but the buttons and menus are generally not designed for use via eye tracking, and may be small or finicky.
The new versions are still based on the web apps, but designed with gaze tracking in mind, with large, clear controls on one side and the app’s normal interface on the right. There are simple directional controls, of course, but also context and app-specific ones, like “genre” when browsing Netflix.
The company highlights one user, Delaina Parrish (in the lead image), who relies on apps like Instagram to build her Fearless Independence brand but has been limited in how easily she could use them due to her cerebral palsy. “These accessible apps have improved my daily productivity, my channels of communicating personally and for business, and my overall independence,” she said in the Tobii press release.
It’s hard to overestimate the difference between a tool or interface that’s “good enough” and able to be used by people with disabilities, and one that’s built with accessibility as a goal from the start. The new apps should be available on compatible devices now.