Alert modification based on social media activity

An alert system and method may include receiving a notification message, identifying a content of the notification message, in response to receiving the notification message, analyzing a social media activity of the user to determine that the content of the notification message is relevant to the social media activity of the user, and alerting, by the processor, the user of the notification message in accordance with a modified alert preference.

TECHNICAL FIELD

The present invention relates to systems and methods for alert modification, and more specifically the embodiments of an alert system for alerting a user based on a relevancy to a social media activity of the user and a content of a notification.

BACKGROUND

Notification sources, such as bluetooth low energy (BLE) beacons provide an enhanced experience for customers of venues, such as stadiums, airports, retail stores, shopping malls, and hospitals. The beacons can be used for a wide range of uses, from sales promotions to building security. Likewise, notifications for software applications are also received.

SUMMARY

An embodiment of the present invention relates to a method, and associated computer system and computer program product, for modifying an alert based on a relevancy to a social media activity of the user and a content of a notification. A processor of a computing system receives a notification message. A content of the notification message is identified in response to receiving the notification message. A social media activity of the user is analyzed to determine that the content of the notification message is relevant to the social media activity of the user. The user is alerted to the notification message in accordance with a modified alert preference.

DETAILED DESCRIPTION

One or more notification sources, such as beacon devices, such as a BLE beacon may be arranged throughout an environment or venue, such as a retail store, airport, shopping mall, stadium, concert, festival, hospital, and the like. When a user mobile device comes within a certain proximity of the beacon device, the user's mobile device may receive and process a signal from the beacon, which can result in receiving a notification message for the user to view on the user's mobile device. Notification messages, such as push notifications can have a dramatic effect on an application's ability to engage users. As user's interests change over time, social media content can be used to help monitor the evolution of user's interest. Further, by knowing that a user is interested in, the alert preferences for alerting the user to the notification message can be modified accordingly.

Thus, there is a need for an alert system for alerting a user based on a relevancy to a social media activity of the user and a content of a notification. The alert system described herein may analyze push notifications and provide the user with a proper alert according to a relevancy to the user's shared social content.

Referring to the drawings,FIG. 1depicts a block diagram of alert system100, in accordance with embodiments of the present invention. Embodiments of the alert system100may be a system for determining an alert preference of the user based on relevancy or relationship between a social media activity of the user and a content of a push notification or other notification message. Embodiments of the alert system100may be useful for users who prefer to only receive certain push notification that pertain to topics that the user is interested in. For example, users can become annoyed if the user is receiving a notification message that the user is not interested in receiving. Further, the effectiveness of the notifications using alert system100is increased because the user is more likely to take advantage of the notification. Notification messages may be signals, communications, transmissions, messages, push notifications, data, notifications, and the like, that contain text, received by a user mobile device from one or more beacon devices or notification sources arranged in an environment of venue. Embodiments of the environment may be a venue, a location, a city, a neighborhood, a district, a shopping center, a warehouse, a building, a school, a campus, a hospital, a base camp, a shopping mall, a retail store, a market, an airport, a train station, a stadium, and the like.

Embodiments of the alert system100may be an alert modification system, a notification content and social media content analysis system, an alert customization system, a notification system, and the like. Embodiments of the alert system100may include a computing system120. Embodiments of the computing system120may be a computer system, a computer, a cellular phone, a user mobile device, a user computing device, a tablet computer, a smart watch, a wearable computing device, such as smart eyeglasses, a dedicated mobile device, a laptop computer, other internet accessible/connectable device or hardware, and the like. Embodiments of the computing system120may include hardware functionality such as a speaker for emitting a sound, a vibration motor for creating vibrations, a display for displaying the notification message, with the ability to flash the display or portions of the content being displayed, a light emitting element for emitting a light, a receiver for receiving communications, a transmitter for transmitting signals, and other similar features and hardware of a smartphone, smartwatch, cell phone, tablet computer, and the like.

Furthermore, embodiments of alert system100may include one or more notification sources110a,110b. . .110n, which are devices (for example, beacon devices) that are communicatively coupled to a computing system120of the alert system100over a computer network107. For instance, information/data may be transmitted to and/or received from one or more notification sources110a,110b. . .110nover a network107. A computer network107may be the cloud. Further embodiments of computer network107may refer to a group of two or more computer systems linked together. Computer network107may be any type of computer network known by individuals skilled in the art. Examples of computer network107may include a LAN, WAN, campus area networks (CAN), home area networks (HAN), metropolitan area networks (MAN), an enterprise network, cloud computing network (either physical or virtual) e.g. the Internet, a cellular communication network such as GSM or CDMA network or a mobile communications data network. The architecture of the computer network107may be a peer-to-peer network in some embodiments, wherein in other embodiments, the computer network107may be organized as a client/server architecture.

In some embodiments, the computer network107may further comprise, in addition to the computing system120, a connection to one or more network-accessible knowledge bases114, which are network repositories containing information of the user, product information, promotional information, social media platform account information, location information, user activity, user preferences, network repositories or other systems connected to the computer network107that may be considered nodes of the computer network107. In some embodiments, where the computing system120or network repositories allocate resources to be used by the other nodes of the computer network107, the computing system120and network-accessible knowledge bases114may be referred to as servers.

The network-accessible knowledge bases114may be a data collection area on the computer network107which may back up and save all the data transmitted back and forth between the nodes of the computer network107. For example, the network repository may be a data center saving and cataloging user activity data, user data, location data, user preference data, and the like, to generate both historical and predictive reports regarding a particular user or a user's message preference, and the like. In some embodiments, a data collection center housing the network-accessible knowledge bases114may include an analytic module capable of analyzing each piece of data being stored by the network-accessible knowledge bases114. Further, the computing system120may be integrated with or as a part of the data collection center housing the network-accessible knowledge bases114. In some alternative embodiments, the network-accessible knowledge bases114may be a local repository that is connected to the computing system120.

Embodiments of the one or more notification sources110a,110b. . .110nmay be a beacon, a beacon device, RF device, hardware transmitter, a BLE device, a transmitter, an emitting device, and the like, which may broadcast a universally unique identifier for receiving by a user mobile device. The one or more notification sources110a,110b. . .110nmay be used for mobile marketing in an environment, broadcasting promotional push notifications to the user mobile devices when the user mobile device is at a particular location or point-of-interest. The one or more notification sources110a,110b. . .110nmay be interconnected over a network, or may be independent and separate from the other beacons or notification sources in a same venue or environment. In other embodiments, the notification source110a,110b. . .110cmay be one or more server servicing an application downloaded on the user device.

Referring still toFIG. 1, embodiments of the alert system100may include a social media platform111. Embodiments of the social media platform111may be communicatively coupled to the computing system120over computer network107. Embodiments of the social media platform111of the alert modification system100depicted inFIG. 1may be one or more social media platforms. Moreover, embodiments of social media platform111may be one or more websites, applications, databases, storage devices, repositories, servers, computers, engines, and the like, that may service, run, store or otherwise contain information and/or data regarding a social media network of the user and the user's social contacts. The social media platform or platforms111may be accessed or may share a communication link over network107, and may be managed and/or controlled by a third party, such as a social media company. In an exemplary embodiment, the social media platform111may be a social media network, social media website, social media engine, and the like, which may store or otherwise contain content supplied by a social contact of the user, as well as content shared by a user on the social media platform111.

Furthermore, embodiments of the computing system120may be equipped with a memory device142which may store various data/information/code, and a processor141for implementing the tasks associated with the alert modification system100. In some embodiments, an alert modification application130may be loaded in the memory device142of the computing system120. The computing system120may further include an operating system, which can be a computer program for controlling an operation of the computing system120, wherein applications loaded onto the computing system120may run on top of the operating system to provide various functions. Furthermore, embodiments of computing system120may include the alert modification application130. Embodiments of the alert modification application130may be an interface, an application, a program, a module, or a combination of modules. In an exemplary embodiment, the alert modification application130may be a software application running on one or more back end servers, servicing a user mobile device, or may be a software application running on the user mobile device.

The alert modification application130of the computing system120may include a receiving module131, a content identification module132, an analytics module133, and an alerting module134. A “module” may refer to a hardware-based module, software-based module or a module may be a combination of hardware and software. Embodiments of hardware-based modules may include self-contained components such as chipsets, specialized circuitry and one or more memory devices, while a software-based module may be part of a program code or linked to the program code containing specific programmed instructions, which may be loaded in the memory device of the computing system120. A module (whether hardware, software, or a combination thereof) may be designed to implement or execute one or more particular functions or routines.

Embodiments of the receiving module131may include one or more components of hardware and/or software program code for receiving a notification message from a notification source, such as notification sources110a,110b, in an environment with one or more notification sources110a,110b. . .110narranged throughout the environment. For instance, embodiments of the receiving module131may receive a transmission from a beacon arranged in an environment when a user reaches a particular physical location within the venue or at a given time from the closest notification source when the notification sources110a,110b. . .110nare broadcasting/transmitting a similar signal. In an exemplary embodiment, the receiving module131may receive and/or process the signal received by the receiver hardware of the user mobile device, for further analysis by the alert modification application130. Furthermore, a notification message can be triggered by events, such as location-based events, context-based events, time-based events, and/or random events.

Referring again toFIG. 1, embodiments of the computing system120may further include a content identification module132. Embodiments of the content identification module132may include one or more components of hardware and/or software program for identifying a content of the notification message, in response to receiving the notification message. For instance, embodiments of the content identification module132may, in response to receiving the notification message from a beacon or other notification transmitting device, analyze the notification message to determine a content of the notification message. The content of the notification message may be analyzed by a text analysis system that may parse, identify, scan, detect, analyze etc. words using, for example, a natural language processing technique, natural language classification, pre-trained language model, etc. to analyze the content payload of the notification message. The content of the notification message may be items, goods, pictures, locations, services, offers, promotions, sales, invitations, and the like. Embodiments of the content identification module132may thus process the notification message so that the computing system120understands the content, such as a meaning of the content.

Embodiments of the computing system120may include an analytics module133. Embodiments of the analytics module133may include one or more components of hardware and/or software program for analyzing a social media activity of the user to determine that the content of the notification message is relevant to the social media activity of the user on one or more social media platforms111. For instance, in response to receiving a notification message and determining the content payload of the notification message, the analytics module133may analyze, parse, scan, review, etc. a user's shared content and the user's activity on a user's social media account(s), as well as a shared content and an activity of the user on social contacts of the user, shared or otherwise available on one or more social media platforms111. The analyzing may be performed to determine that a content shared by the user across the social media platform111is relevant or otherwise correlates to the content of the notification message. In an exemplary embodiment, the analytics module133may analyze a user's social media network activity via content shared by the user on the user's social media page as well as on social contacts' social media page. The analytics module133may ascertain a context of the shared content, and then determine whether the context of the shared content correlates or is relevant to the content of the notification message received by the user device of the user. The shared content shared, uploaded, or otherwise posted on the social media platform111may be photographs, videos, comments made on other contacts' pages, text-based posts made to the social contact's own social media page, and the like. The shared content may be analyzed, parsed, scanned, searched, inspected, etc. for a context that correlates or otherwise relates to or is associated with the content of the received notification message. In an exemplary embodiment, the analytics module133may utilize a natural language technique to determine keywords associated with the content available on the social media platform111, and then examine the determined keywords with keywords that may be relatable with content encompassed by the notification message. In another exemplary embodiment, the analytics module133may utilize an image or visual recognition engine to inspect, parse, scan, analyze, etc. a photograph, image, video, or other content to determine one or more descriptions or insights that describe or are associated with the photograph, image, video, or other content, and then examine the descriptions/insights with keywords that may be relatable with the content encompassed by the notification message. In yet another embodiment, the analytics module133may use a combination of natural language techniques, cognitive applications/engines, and visual recognition engines to determine a context, content, and relevancy of the shared content available on the one or more social media platforms for comparison with the content of the notification message.

Moreover, embodiments of the analytics module133may compare the determined context and content from the shared content with the content of the notification message received by the receiving module131. For instance, keywords, texts, insights, or other acquired computer readable information associated with the analyzed shared social media content and user social media activity may be compared with keywords, texts, insights, or other computer readable information associated with the content of the notification message. Based on the comparison, the analytics module133may determine that the content of a particular social media content supplied by the user on the user's social media network may be relevant or otherwise correlate to the content of the received notification message.

Turning now toFIGS. 2-3for an example of analyzing a social media activity of the user (e.g. posts, shared content, frequency of logins, etc.) on one or more social media platforms111to determine that the content of the notification message is relevant to the social media activity of the user on one or more social media platforms111.FIG. 2depicts a first notification message150received by a user device152, in accordance with embodiments of the present invention. Here, the content of the notification message150relates to an offer for outdoor apparel being sold at a nearby store.FIG. 3depicts a social media page200of a user, containing shared content220,221,230, in accordance with embodiments of the present invention. The social media page200may include a name or identity201of the user and contact information202. The analytics module133may analyze the social media page200to determine whether the user's social media page200contains any content or activity that may be relevant to outdoor apparel. Here, the shared content on the user's social media page200includes two photo albums220,221with multiple photographs. The first photo album220has a cover photo of a mountain. The analytics module133of the computing system120may determine (e.g. based on WATSON visual recognition and insights) that the cover photo is of a mountain, and the photographs of the album are mostly of mountains. The analytics module133may then correlate the mountains contained in the photographs (i.e. a context of the shared content) with outdoor apparel (i.e. subject or content of the notification message). Similarly, the second photo album221has a cover photo of a person walking on a trail in the outdoors. The analytics module133of the computing system120may determine (e.g. based on WATSON visual recognition and insights) that the cover photo is of a person walking outside, and the photographs of the album are mostly of the social contact walking outside. The analytics module133may then correlate the user or person walking outside in many of the photographs (i.e. a context of the shared content) with hiking and outdoors (i.e. content of the notification message). Furthermore, embodiments of the analytics module133may analyze comments230posted by user on the user's social media page200. In the comments, the user has posted text relating to “hiking boots,” “Grand Canyon,” “parka,” “Brand Y,” and “hiking,” These keywords may be associated with a context of outdoor activities, which can correlate to or is relevant to the purchasing outdoor apparel at a discount, which is the content of the notification message150.

FIG. 4depicts a third notification message150received by a user device152, in accordance with embodiments of the present invention. Here, the content of the notification message150relates to a home remodeling class to learn how to install floor tiles. The analytics module133may analyze the social media page200to determine whether the user's social media page200contains any content or activity that may be relevant to home remodeling. Here, the shared content on the user's social media page200includes comments230posted by user on the user's social media page200that may be relevant to home remodeling. In the comments230, the user has posted text relating to “working,” “home,” “enjoy,” and “kitchen sink.” These keywords may be associated with a context of home remodeling, which can correlate to or is relevant to signing up for a free class to learn about additional home remodeling projects, which is the content of the notification message150.

Furthermore, embodiments of the analytics module133may also perform a sentiment analysis to the content on the user's social media page200to determine a sentiment and/or intention. Sentiment analysis may be performed by the analytics module133to help the computing system120understand and/or learn a sentiment of the shared content and/or the user. A sentiment may refer to whether the shared content, a feeling of the user, an attitude of the user, a context of the shared content, and/or mental state of the user is positive, negative, or neutral. The sentiment may be derived from natural language processing and sentiment analysis techniques, and may be evaluated or scored on a range or sentiment scale. An intention may refer to an act that a user may take, such as a buying a product, going to a movie, taking a trip, and the like. In the comments230, the user has used the word “enjoy” when referring to or describing “working,” “home,” and “kitchen sink.” The analytics module133may conclude that the user has a positive feeling about working on home projects, and thus may be receptive to a notification message150that is relevant to home projects and remodeling. Similarly, in the comments230, the user has used the word “need” when referring to or describing “new,” and “hiking boots.” The analytics module133may conclude that the user intends to purchase new hiking boots, and thus may be very receptive to a notification message150that is relevant to a discount on outdoor apparel.

Turning now toFIGS. 5-6for another example of analyzing a social media activity of the user (e.g. posts, shared content, frequency of logins, etc.) on one or more social media platforms111to determine that the content of the notification message is relevant to the social media activity of the user on one or more social media platforms111.FIG. 5depicts a third notification message150received by a user device152, in accordance with embodiments of the present invention. Here, the content of the notification message150relates to airline travel and vacation packages.FIG. 6depicts a social media page200aof a social media contact201aof the user, containing shared content220,221,230, in accordance with embodiments of the present invention. The social media page200amay include a name or identity201aof the social media contact of the user and contact information202. The analytics module133may analyze the social media page200abecause the user has been active on the social media page201a. The analytics module133may determine whether the user's activity on social media page200acontains any content or activity that may be relevant to traveling. Here, in the comments230on page200a, the user has posted text relating to “take,” “trip,” and “Las Vegas.” These keywords may be associated with a context of airline travel, which can correlate to or is relevant to the purchasing airline tickets, which is the content of the notification message150.

FIG. 7depicts a fourth notification message150received by a user device152, in accordance with embodiments of the present invention. Here, the content of the notification message150relates to a eating seafood at a restaurant. The analytics module133may analyze the social media page200abecause the user has been active on the page200a. The analytics module132may determine that the social media page200acontains content or activity from the user that may be relevant to seafood. Here, the content shared by the user on the user's social media contact's page200aincludes comments230posted by user that may be considered relevant to eating seafood. In the comments230, the user has posted text relating to “crab legs,” and “seafood.” These keywords may be associated with a context of eating seafood, which can correlate to or is relevant to having a seafood meal, which is the content of the notification message150inFIG. 7.

Furthermore, embodiments of the analytics module133may also perform a sentiment analysis to the content on social media page200ato determine a sentiment and/or intention. Sentiment analysis may be performed by the analytics module133to help the computing system120understand and/or learn a sentiment of the shared content and/or the user. In the comments230, the user has used the word “never go wrong” and “good” when referring to or describing “seafood.” The analytics module133may conclude that the user has a positive feeling about eating seafood, and thus may be receptive to a notification message150that is relevant to restaurants serving fresh seafood. Similarly, in the comments230, the user has used the word “love” and “take a trip” when referring to or describing “Las Vegas.” The analytics module133may conclude that the user intends to take a trip to Las Vegas, and thus may be very receptive to a notification message150that is relevant to a discount on airfare, which is the content of the notification message150inFIG. 5.

Moreover, embodiments of the analytics module133may analyze a recent history of shared social media content and activity of the user for a specified data range measured from receiving the notification message. For instance, the analytics module133may analyze the social media activity of the user for a period of time, measured backwards from the time of the receiving the notification message, such as an hour, a day, a week, a couple of weeks, a month, a couple of months, a year, and the like. By analyzing a recent social media activity of the user, the computing system120may follow or track changes in the user's interests, needs, etc. over time. Further, social media activity may include recent text posts, recent check-ins, recent photo uploads, recent “liked” items, and recent re-shares.

Referring back toFIG. 1, embodiments of the computing system120may also include an alerting module134. Embodiments of the alerting module134may include one or more components of hardware and/or software program code for alerting the user of the notification message in accordance with a modified alert preference. For instance, embodiments of the alerting module134may notify or otherwise alert the user to the notification using a specific, custom alert based on a determined relevance to social media activity of the user. By alerting the user with a specific alert preference, the user may then know that the notification is likely to be important or otherwise worth checking. The modified alert preferences may include variations of sensory, audible, haptic, etc. feedback, to assist the user in deciding whether it is worth the user's time to check the notification and carefully examine the notification, especially in situations where the user is inundated with notifications from various sources. In an exemplary embodiment, the alerting module134may display the notification on a screen of the user's mobile device, along with a perceptible sensory action, including a tone, a sound, a vibration, an emission of light, a sporadic emission of light, etc. The alerting module134may instruct various hardware functionalities to perform various tasks to implement the modified alert preference associated with notification. For example, the alerting module134may instruct the mobile device hardware, such as a light element, a display, a vibration motor, a speaker, associated software, and the like.

Furthermore, the modified alert preference modified based on the relevancy to social media activity of the user may be distinguishable from a default alert preference that is used for notification messages that are determined to not be relevant to the social media activity. In other words, the modified alert preference may be more prominent than a default alert. Embodiments of the alerting module134may determine that a default alert preference should be modified based on the determination that the notification message is relevant to recent social media activity/shared content of the user.

Embodiments of an alert or alert preference may include a short vibration, a long vibration, a short vibration and a ringtone, a long vibration and a ringtone, a silent notification, a flashing notification (e.g. notification banner flashing), a silent notification and a flashing notification, a tone, a color (e.g. color of banner background of notification message of a particular color), and a combination thereof. Further, alert preferences may involve a change in volume (e.g. tone gradually increases, or starts at a higher volume level than a setting on the phone), a change in font size, a change in font style, such as bold, italics, and underlined font, a change in vibration strength and/or duration, a strobe effect using a light element on the user mobile device, a change in vibration frequency, and the like.

In an exemplary embodiment, the default alert preference may be selected by the user or may be automatically set by the computing system120to correspond to a situation where the content of the notification message is not relevant to the social media activity of the user. For example, the user may interact with the user mobile device GUI of alert modification application130to enter which alerts the user would prefer to receive for a particular type of notification message received.FIG. 8depicts a fifth type of notification message150along with a pictorial representation of a corresponding alert preference, in accordance with embodiments of the present invention. Here, the notification message150elicits no notification to the user (depicted as an alarm bell having a ling through the alarm bell). The analytics module133has analyzed the social media activity of the user, as depicted inFIGS. 3 and 6, and determined that the content of the notification message150(i.e. baseball tickets) is not relevant to the social media activity of the user on one or more social media platforms111. The alerting module134may use a silent notification, or no notification beyond appearing as a banner on a screen of the user's mobile device, because of a lack of relevancy to the social media activity of the user.

FIG. 9depicts the first notification message ofFIG. 2, along with a pictorial representation of a corresponding alert preference, in accordance with embodiments of the present invention. Here, the content of the notification message150has been determined to be relevant, so the alerting module134modifies the default alert preference, such as the alert depicted inFIG. 8to a modified alert preference. In this example, the modified alert preference elicits an audible tone for ten seconds in combination with a short vibration, and a specific color coded banner (depicted as a single alarm bell and 10 s, along with a single alarm bell having vibration effect, and “blue”). Embodiments of the alerting module134may modify the default or low impact alert in many ways, so long as the user may perceive a difference between the alerts. Embodiments of modified alert or modified alert preference may have a varying time duration for making audible sound, and may be a short vibration, a long vibration, a short vibration and a ringtone, a long vibration and a ringtone, a silent notification, a flashing notification, a silent notification and a flashing notification, a tone, a color, and a combination thereof. Further, the alerting module134may modify the alert by changing the volume, increasing the volume, changing a font size, changing a font style, such as bold, italics, and underlined font, changing an amplitude or frequency of the vibration, changing a force of the vibration, increasing a length of the vibration, repeat various modifications, and the like.

FIG. 10depicts the notification ofFIG. 9, along with an explanation as to why the alert was modified, in accordance with embodiments of the present invention. Along with the modification to the alert method (e.g. how the notification is presented to the user), embodiments of the alerting module134may attach additional metadata as to why the alert was modified. For example, the notification message150ofFIG. 10depicts a reason why the notification alert was modified and/or made more prominent, that is, the content of the notification was relevant to a recent social media post regarding hiking boots and outdoor activities.

Various tasks and specific functions of the modules of the computing system120may be performed by additional modules, or may be combined into other module(s) to reduce the number of modules. Further, embodiments of the computer or computer system120may comprise specialized, non-generic hardware and circuitry (i.e., specialized discrete non-generic analog, digital, and logic-based circuitry) (independently or in combination) particularized for executing only methods of the present invention. The specialized discrete non-generic analog, digital, and logic-based circuitry may include proprietary specially designed components (e.g., a specialized integrated circuit, such as for example an Application Specific Integrated Circuit (ASIC), designed for only implementing methods of the present invention). Moreover, embodiments of the alert system100offers a method to filter push notifications received from notification sources based on a social media activity. The alert modification system100may be individualized to each user/user device, which is being used to filter notifications based on a social media activity, by analyzing the content of the push notification and using device hardware to notify the user.

Furthermore, the alert modification system100improves computer technology by saving computing power resources. Issuing an alert to the user uses power and other computing resources of a mobile device. Additional power is also used if the user activates the device from a rest state with the screen turned off to an active state to check the alert. The claimed solution is necessarily rooted in computer technology in order to overcome a problem specifically arising in the realm of computer technology. By reducing the number of alerts presented to the user using a specific set of rules, there is a savings in the computing resources used. For example, in the embodiment shown inFIG. 8, the alert modification application130does not use computing power to sound an alarm, cause the mobile to vibrate, etc., which may normally occur without the alert modification application130because the alert modification system100has determined that a particular user is not likely to be interested. In other words, the alert modification application130may determine that a notification message150received by the user should be presented to the user in accordance with an alert preference that may consume less computing resources than if the notification message150was presented to the user in a traditional manner (i.e. without analyzing the content payload of the notification message150and the social media activity of the user across one or more social media platform111). Thus, in some embodiments, there is an improvement to the computing device/systems overall, because the alert system100may be directed to an improvement to computer technology, including software that improves the capability of a computing device.

Referring now toFIG. 11, which depicts a flow chart of a method300for alert modification based on a social media activity of a user, in accordance with embodiments of the present invention. One embodiment of a method300or algorithm that may be implemented for alert modification based on a social media activity of a user with the alert modification system100described inFIGS. 1-10using one or more computer systems as defined generically inFIG. 13below, and more specifically by the specific embodiments ofFIG. 1.

Embodiments of the method300for alert modification based on a social media activity of a user, in accordance with embodiments of the present invention, may begin at step301wherein a notification is received by the user mobile device from one or more notification sources110a,110b. . .110n. Step302identifies a content of the notification message. Step303analyzes a social media activity of the user to determine a relevancy of notification message, based on the content/activity of the user on one or more social media platforms111. Step304modifies an alert preference when alerting the user to denote a significance of the incoming notification message.

FIG. 12depicts a detailed flow chart of a method400for alert modification based on a social media activity of a user, in accordance with embodiments of the present invention. Embodiments of the method400for alert modification based on a social media activity of a user may begin at step401, wherein the notification message is received a notification source110a,110b. . .110n. Step402analyzes the body or content payload of the notification message to determine a content of the notification message. Step403checks a social media platform111for user activity, for example a recent activity. Step404determines whether the notification message is relevant to the social media activity. If no, step405alerts user according to default settings, with no customized alert preference or prominent alert method. If yes, step406modifies the alert preference from the default alert preference to a modified alert preference. Step407alerts the user accordingly.

FIG. 13depicts a block diagram of a computer system for the alert modification system100ofFIGS. 1-10, capable of implementing methods for alert modification based on a social media activity of a user ofFIGS. 11-12, in accordance with embodiments of the present invention. The computer system500may generally comprise a processor591, an input device592coupled to the processor591, an output device593coupled to the processor591, and memory devices594and595each coupled to the processor591. The input device592, output device593and memory devices594,595may each be coupled to the processor591via a bus. Processor591may perform computations and control the functions of computer system500, including executing instructions included in the computer code597for the tools and programs capable of implementing a method for alert modification based on a social media activity of a user in the manner prescribed by the embodiments ofFIGS. 11-12using the alert modification system100ofFIGS. 1-10, wherein the instructions of the computer code597may be executed by processor591via memory device595. The computer code597may include software or program instructions that may implement one or more algorithms for implementing the method for alert modification based on a social media activity of a user, as described in detail above. The processor591executes the computer code597. Processor591may include a single processing unit, or may be distributed across one or more processing units in one or more locations (e.g., on a client and server).

The memory device594may include input data596. The input data596includes any inputs required by the computer code597. The output device593displays output from the computer code597. Either or both memory devices594and595may be used as a computer usable storage medium (or program storage device) having a computer-readable program embodied therein and/or having other data stored therein, wherein the computer-readable program comprises the computer code597. Generally, a computer program product (or, alternatively, an article of manufacture) of the computer system500may comprise said computer usable storage medium (or said program storage device).

Memory devices594,595include any known computer-readable storage medium, including those described in detail below. In one embodiment, cache memory elements of memory devices594,595may provide temporary storage of at least some program code (e.g., computer code597) in order to reduce the number of times code must be retrieved from bulk storage while instructions of the computer code597are executed. Moreover, similar to processor591, memory devices594,595may reside at a single physical location, including one or more types of data storage, or be distributed across a plurality of physical systems in various forms. Further, memory devices594,595can include data distributed across, for example, a local area network (LAN) or a wide area network (WAN). Further, memory devices594,595may include an operating system (not shown) and may include other systems not shown inFIG. 13.

In some embodiments, the computer system500may further be coupled to an Input/output (I/O) interface and a computer data storage unit. An I/O interface may include any system for exchanging information to or from an input device592or output device593. The input device592may be, inter alia, a keyboard, a mouse, etc. or in some embodiments the touchscreen of a computing device. The output device593may be, inter alia, a printer, a plotter, a display device (such as a computer screen), a magnetic tape, a removable hard disk, a floppy disk, etc. The memory devices594and595may be, inter alia, a hard disk, a floppy disk, a magnetic tape, an optical storage such as a compact disc (CD) or a digital video disc (DVD), a dynamic random access memory (DRAM), a read-only memory (ROM), etc. The bus may provide a communication link between each of the components in computer500, and may include any type of transmission link, including electrical, optical, wireless, etc.

An I/O interface may allow computer system500to store information (e.g., data or program instructions such as program code597) on and retrieve the information from computer data storage unit (not shown). Computer data storage unit includes a known computer-readable storage medium, which is described below. In one embodiment, computer data storage unit may be a non-volatile data storage device, such as a magnetic disk drive (i.e., hard disk drive) or an optical disc drive (e.g., a CD-ROM drive which receives a CD-ROM disk). In other embodiments, the data storage unit may include a knowledge base or data repository125as shown inFIG. 1.

As will be appreciated by one skilled in the art, in a first embodiment, the present invention may be a method; in a second embodiment, the present invention may be a system; and in a third embodiment, the present invention may be a computer program product. Any of the components of the embodiments of the present invention can be deployed, managed, serviced, etc. by a service provider that offers to deploy or integrate computing infrastructure with respect to alert modification systems and methods. Thus, an embodiment of the present invention discloses a process for supporting computer infrastructure, where the process includes providing at least one support service for at least one of integrating, hosting, maintaining and deploying computer-readable code (e.g., program code597) in a computer system (e.g., computer system500) including one or more processor(s)591, wherein the processor(s) carry out instructions contained in the computer code597causing the computer system to modify alerts based on a type of notification. Another embodiment discloses a process for supporting computer infrastructure, where the process includes integrating computer-readable program code into a computer system500including a processor.

The step of integrating includes storing the program code in a computer-readable storage device of the computer system500through use of the processor. The program code, upon being executed by the processor, implements a method for alert modification based on a social media activity of a user. Thus, the present invention discloses a process for supporting, deploying and/or integrating computer infrastructure, integrating, hosting, maintaining, and deploying computer-readable code into the computer system500, wherein the code in combination with the computer system500is capable of performing a method for alert modification based on a social media activity of a user.

A computer program product of the present invention comprises one or more computer-readable hardware storage devices having computer-readable program code stored therein, said program code containing instructions executable by one or more processors of a computer system to implement the methods of the present invention.

Characteristics are as follows:

Service Models are as follows:

Deployment Models are as follows:

Referring now toFIG. 15, a set of functional abstraction layers provided by cloud computing environment50(seeFIG. 14) are shown. It should be understood in advance that the components, layers, and functions shown inFIG. 15are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: