Social Media versus Mainstream News and Google Search
We examined the quality and speed of original news stories and information on social media now delivering content directly to users in near real-time versus mainstream news outlets that are often constrained by a variety of filters, delays and influenced by power brokers.
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Although for example, Twitter social data analytics uncover the need to encourage more in-depth original information and localized news stories versus duplicate retweet postings.
Case studies show Twitter does “beat the mainstream news?” in speed of real-time news stories and information dissemination. However, overall we find about 70% of Twitter traffic are retweets or replies, rather than new original content stories or educational materials.
Today, about 75%, or 247 million people in the U.S. have a social media account. And much of the Twitter attention based on social analytics data has found it to be highly reactive, waiting until a major activity is occurring before registering a post signal. Social media networks tends to surge quickly and dissipate just as quickly, operating more like an alarm or a behavioral and attention signal, using event stream approaches to understanding its insights.
So, we suggest further developing Twitter search, original information content creation and local group tools. Community localization would bring forth interesting unique grassroots stories, often lacking in main stream media, essentially make every user a valuable local news and information source highlighting neighborhood issues and concerns added J Dean @SCS.
A grassroots based social news and information channel would attract significant advertising interest from local business owners and major brands, thus increasing Twitter's revenue by 50% or more. By creating a more "townhall" community based information resource, Twitter can serve to better add value enabling unfiltered civil dialogue and drive a more localized marketplace experience that directly benefits individuals, families and businesses.
Data analytics shows localized community based news posted on Twitter often draws 65% or more views than national news stories concerning issues outside the users local community.
We also recommend better leveraging and delivery of news information that's driven by Twitter users profile details including geographic location would help shape a more localized, grassroots community townhall experience that incentivizes the users to share local stories.
A greater focus on development of Twitter Communities or groups, which were previously known as Twitter Lists will help users build and engage with more localized communities.
While social media can offer a real-time glimpse into events as they happen, it is not always the first or most reliable source of breaking news. Social media is just one of many data streams that can be used to study trends, but each source has strengths and limitations.
For example, it's important to accurately report and help educate people on medical and wellness matters. In fact, social network media has become a source for healthcare materials.
Still, mainstream news media can provide more in-depth coverage and analysis of breaking news, whereas social media tends to be more immediate and raw posts. Search trend data can also offer insights into what topics people are interested in and searching for online. But we found that Google keyword searches had dropped to under 30% as a primary source.
When it comes to Twitter specifically, it is more difficult to pinpoint the precise moment when a story breaks, as the platform's stream-of-consciousness format can make it hard to identify the first mention of a particular event. As the example of a dam burst illustrates, it may take some time for a story to emerge and for the full picture to become clear.
In summary, while social media can offer valuable insights into societal trends and events, it is important to approach it with a critical eye and to consider other data streams as well. It is also important to recognize the limitations of social media, including the challenges in identifying the first mention of a story and the potential for misinformation to spread rapidly on these platforms. Verification on the source of the content information adds credibility. This highlights the need for social media networks to better validate users with Digital ID.
This analysis highlights the challenges of using social media as a primary source for understanding breaking events. While social media can provide real-time insights into what people are saying and sharing about a particular event, it can be difficult to identify the first mentions of an event due to the stream-of-consciousness nature of the social networks.
The language and vocabulary used on social media can be different from that used in news media or web search trends, making it difficult to directly compare the different data streams. But we did test the speed of social networks like Twitters vs. mainstream media.
The speed test on news dissemination shows, for example, the first Tweet on the Tyre Nichols story in Memphis Tennessee appeared on January 15, 2023 at 6:10AM. Then subsequently, main stream media stories began to appear January 16, 2023 on CBS News.
Again on the recent February 4, 2023 Ohio train wreck that spilled toxic chemicals in the small town of East Palestine, we find the first Tweet on Feb. 4, 2023 at 8:08PM. Then subsequently the story was reported by Associated Press / NBC on February 5, 2023 at 2:51PM. So, again data analytics prove that Twitter's localized reach is near real-time.
Examining world events such as the case of the Green New Deal press conference, news media provided an earlier signal of the event than Twitter, which was largely reactive. The breakdown of tweets by type also reveals that much of Twitter's speed in this case came from retweeting previous posts, rather than providing new insights.
This highlights the importance of considering multiple data streams and using a critical eye when analyzing social media data. While social media can be a valuable tool for understanding societal trends and events, it should not be viewed as the sole source of information or the definitive source of breaking news.
For example studying a variety of events including Hurricane Harvey’s August 2017 in Houston Texas floods in 2017 demonstrated the different ways that news, web searches, and Twitter react to a major disaster like flooding in Houston.
The media provides continuous coverage before and after the flooding, while web searches show a rapid increase in interest as the news of the flooding emerges. Twitter lags behind the other sources, only beginning to surge in the morning after the flooding, as people react to news articles and images of the destruction.
The difference in the types of tweets during the flooding also highlights how Twitter can be used as a behavioral dataset, as opposed to a content dataset. During the early surge of tweets, many of them were retweets or forwarded links, rather than original commentary.
Later on, tweets became more personalized, with the majority including links or images, indicating that people were sharing information and visuals of the flooding with their networks.
Overall, the passage demonstrates how each medium can provide unique insights into major events, but also highlights their limitations and the challenges of comparing and interpreting their data.
And it seems that in the case of the Townsville flooding, Google searches and news coverage were more closely aligned than Twitter activity, which did not respond as significantly. This could suggest that Twitter was not as effective at disseminating information about the event or that the audience for this type of information was not as active on the platform. It is also interesting to note that the majority of attention seemed to be local to Australia, as most of the activity began around 7AM Australian time.
As the flooding became more severe and the city began evacuations downstream, search activity surged and remained highly elevated throughout the day on February 2nd, with a surge of news coverage as well, but little increase in tweets. This suggests that while Twitter may be fast, it may not in its current form always be the most effective platform for disseminating information in all situations.
While Twitter activity increased as new developments and government warnings emerged. The use of retweets and the sharing of links and images on Twitter also seems to be a common trend in disaster situations. It's interesting to see how different forms of media can complement each other in providing a fuller picture of unfolding events.
Researching data analytics over years showed mainstream news media often provides advanced warning of world events before they happen, while social media Facebook, Twitter, YouTube and Reddit offers a quick response to more localized events as they occur.
Google web searches provide insight into the public's interest and consumption of information related to events. However, much of the signal on Twitter is not original commentary but rather forwarding of stories from elsewhere. This suggests that Twitter should be treated as a behavioral and attention signal rather than a content signal.
The popular narrative that Twitter "beats the news" and offers a live view of events as they unfold is more nuanced than it seems. Ultimately, the case studies and data analytics show that the narratives surrounding big data often contain a grain of truth but further development is necessary to fulfill a more in-depth accurate content presentation by social networks, and the advantage social media has lies in its localized user base which can effectively make everyone a report, content creator. This key advantage held by social media networks such as Twitter, Facebook, and Instagram should be better incentivized to draw greater advertising revenue from small business owners and major brand retailers alike.
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