[001] The present invention generally relates to social networking and more particularly, to a
method and a system for partitioning a social network group.
BACKGROUND OF INVENTION
[002] This section is intended to provide information relating to the field of the invention and
thus any approach/functionality described below should not be assumed to be qualified as
prior art merely by its inclusion in this section.
[003] Social networking platforms have become very common among users not only for
communication but also for entertainment, sharing personal views, and so on. From texting
to sharing multimedia contents, it gives various opportunities to the users to express their
feelings/thoughts with each other. In most of the social networking platforms, users can
create social network groups with their friends/relatives/families with whom they would
like to interact or share information on a common platform.
[004] However, many a times, it has been observed that people tend to show less interest in such
a large group. Though the members/users of such created groups know each other, but that
does not guarantee that all of them have similar interest. Some users might want to discuss
or share their experience on a particular topic (e.g., watching movies). However, they may
not feel comfortable discussing such topic in the larger group, in which, other people may
not be interested. Also, in such a large group, due to the fact that different members interact
on a variety of topics, a lot of unnecessary content is also generated. For instance, a member
who is not interested in say for example, interaction on the topic of politics may find the
content shared on politics in the group to be noise and find it frustrating to identify content
relevant to his/her interest being shared in the group. This may result in the member getting
disengaged from such a group. Therefore, identifying users/members in a social network
group with common interest is a technical challenge. Since the users are connected through
different networks, it becomes a challenge to monitor user activities at different network
levels and to understand common interest among the users. The present invention aims to
overcome such technical challenge.
2
OBJECTS OF THE INVENTION
[005] An object of the present invention is to provide a method for partitioning a large social
network group having a large number of members into subgroups with fewer members
having similar interest.
[006] Another object of the present invention is to provide a method for generating social interest
graph of the members to understand their current need/interest.
[007] Yet another object of the present disclosure is to improve user experience by putting the
members from larger group to smaller groups with potentially lesser noise.
SUMMARY OF INVENTION
[008] One or more shortcomings discussed above are overcome, and additional advantages are
provided by the present disclosure. Additional features and advantages are realized through
the techniques of the present disclosure. Other embodiments and aspects of the disclosure
are described in detail herein and are considered a part of the disclosure.
[009] In one non-limiting embodiment of the present disclosure, a method for partitioning a
social network group comprising a plurality of members is disclosed. The method
comprises monitoring interaction content of each member with other members in the social
network group over a predefined time period, wherein the interaction content comprises at
least one of a chat content and a multimedia content associated with one or more topics,
shared by each member while interacting with the other members. The method further
comprises analyzing the interaction content by using Natural Language Processing (NLP)
technique for creating a plurality of interest graphs corresponding to the plurality of
members in such a manner that each interest graph indicates a level of interest of each
member against the one or more topics. The method further comprises correlating the
plurality of interest graphs with each other in order to identify commonality amongst the
plurality of members vis-a-vis the one or more topics. Further, the method comprises
creating one or more subgroups out of the social network group in such a manner that each
3
subgroup comprises a set of members, of the plurality of members, having commonality in
the one or more topics identified while correlating the plurality of interest graphs.
[0010] In one non-limiting embodiment of the present disclosure, a system for partitioning a social
network group comprising a plurality of members is disclosed. The system comprises a
monitoring unit configured to monitor interaction content of each member with other
members in the social network group over a predefined time period, wherein the interaction
content comprises at least one of a chat content and a multimedia content associated with
one or more topics, shared by each member while interacting with the other members. The
system further comprises a graph creation unit configured to analyze the interaction content
by using Natural Language Processing (NLP) technique to create a plurality of interest
graphs corresponding to the plurality of members in such a manner that each interest graph
indicates a level of interest of each member against the one or more topics. The system
further comprises a correlation unit configured to correlate the plurality of interest graphs
with each other in order to identify commonality amongst the plurality of members vis-avis the one or more topics. The system further comprises a group creation unit configured
to create one or more subgroups out of the social network group in such a manner that each
subgroup comprises a set of members, of the plurality of members, having commonality in
the one or more topics identified while correlating the plurality of interest graphs.

[0011] The foregoing summary is illustrative only and is not intended to be in any way limiting.
In addition to the illustrative aspects, embodiments, and features described above, further
aspects, embodiments, and features will become apparent by reference to the drawings and
the following detailed description.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The embodiments of the disclosure itself, as well as a preferred mode of use, further
objectives and advantages thereof, will best be understood by reference to the following
detailed description of an illustrative embodiment when read in conjunction with the
accompanying drawings. One or more embodiments are now described, by way of example
only, with reference to the accompanying drawings in which:
4
[0013] Figure 1 shows an exemplary environment 100 of a system for partitioning a social
network group in accordance with an embodiment of the present disclosure;
[0014] Figure 2 shows a block diagram 200 illustrating a system for partitioning a social network
group in accordance with an embodiment of the present disclosure;
[0015] Figure 3 depicts an exemplary illustration 300 of the interest graphs in accordance with an
embodiment of the present disclosure; and
[0016] Figure 4 shows a method 400 for partitioning a social network group in accordance with
an embodiment of the present disclosure.
[0017] The figures depict embodiments of the disclosure for purposes of illustration only. One
skilled in the art will readily recognize from the following description that alternative
embodiments of the structures and methods illustrated herein may be employed without
departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION
[0018] The foregoing has broadly outlined the features and technical advantages of the present
disclosure in order that the detailed description of the disclosure that follows may be better
understood. It should be appreciated by those skilled in the art that the conception and
specific embodiment disclosed may be readily utilized as a basis for modifying or
designing other structures for carrying out the same purposes of the present disclosure.
[0019] The novel features which are believed to be characteristic of the disclosure, both as to its
organization and method of operation, together with further objects and advantages will be
better understood from the following description when considered in connection with the
accompanying figures. It is to be expressly understood, however, that each of the figures
is provided for the purpose of illustration and description only and is not intended as a
definition of the limits of the present disclosure.
[0020] In the present document, the word "exemplary" is used herein to mean "serving as an
example, instance, or illustration". Any embodiment or implementation of the present
5
subject matter described herein as "exemplary" is not necessarily to be construed as
preferred or advantageous over other embodiments.
[0021] Further, the terms like “comprises”, “comprising”, or any other variations thereof, are
intended to cover non-exclusive inclusions, such that a setup, device that comprises a list
of components that does not include only those components but may include other
components not expressly listed or inherent to such setup or device. In other words, one or
more elements in a system or apparatus proceeded by “comprises… a” does not, without
more constraints, preclude the existence of other elements or additional elements in the
system or apparatus or device.
[0022] Disclosed herein is a method and system for partitioning a social network group. Growth
in the technologies pertaining to digital communications have provided users with various
means to interact with each other on various social networking platforms by using various
means such as audio chats/calls, video chats/calls, and text messages. Also, most of the
social networking platforms, allow users to create/join social network groups with their
friends/relatives/families with whom they would like to interact or share information on a
common platform. However, since such groups tend to have a large number of members
with varied interests, interaction within such a large group often becomes noisy. This
generally happens as the members within such a group, though they may know each other
but may be interested in different topics. For instance, certain members may be interested
in interaction about movies, while others may be interested in interaction about travel or
books or politics etc. Now, when members interested in say for example, politics are
interacting within the group, their conversation or the multimedia content shared by them
would not be of interest to other members that are not interested in political conversation
and therefore, be disinterested in interacting amongst the group or even dissociate from the
group. Further, there might also be a situation where certain members want to interact on
a sensitive topic but are not comfortable in doing so in such a large group. Therefore, it
becomes highly imperative to understand the needs and interests of the members within a
group and thereafter partition the group into smaller subgroups in such a manner that
members within the smaller subgroups share a common topic of interest and are therefore,
comfortable in interacting within the group.
6
[0023] The present disclosure understands this need and provides a system that monitors
interaction of each member of a social network group with other members and determines
the topics of interests for each member by plotting an interest graph. Based on the interest
graphs, smaller subgroups are created such that each subgroup comprises a set of members
interested in one particular topic. The detailed working of the system has been explained
in the upcoming paragraphs.
[0024] Figure 1 shows an exemplary environment 100 of a system for partitioning a social
network group, in accordance with an embodiment of the present disclosure. It must be
understood to a person skilled in art that the system may also be implemented in various
environments, other than as shown in Fig. 1.
[0025] The detailed explanation of the exemplary environment 100 is explained in conjunction
with Figure 2 that shows a block diagram 200 of a system 102 for partitioning a social
network group, in accordance with an embodiment of the present disclosure. Although the
present disclosure is explained considering that the system 102 is implemented on a server,
it may be understood that the system 102 may be implemented in a variety of computing
systems, such as a laptop computer, a desktop computer, a notebook, a workstation, a
mainframe computer, a server, a network server, a cloud-based computing environment.
[0026] In one implementation, the system 102 may comprise an I/O interface 202, a processor
204, a memory 206 and the units 214. The memory 206 may be communicatively coupled
to the processor 204 and the units 214. Further, the memory 206 may store interaction
content 208, member profile 210 and interest graphs 108. The interaction content 208
comprises chat content 208A and multimedia content 208B. The significance and use of
each of the stored quantities is explained in the upcoming paragraphs of the specification.
The processor 204 may be implemented as one or more microprocessors, microcomputers,
microcontrollers, digital signal processors, central processing units, state machines, logic
circuitries, and/or any devices that manipulate signals based on operational instructions.
Among other capabilities, the processor 204 is configured to fetch and execute computerreadable instructions stored in the memory 206. The I/O interface 202 may include a variety
7
of software and hardware interfaces, for example, a web interface, a graphical user
interface, and the like. The I/O interface 202 may enable the system 102 to communicate
with other devices, such as web servers and external data servers (not shown). The I/O
interface 202 may facilitate multiple communications within a wide variety of networks
and protocol types, including wired networks, for example, LAN, cable, etc., and wireless
networks, such as WLAN, cellular, or satellite. The I/O interface 202 may include one or
more ports for connecting many devices to one another or to another server.
[0027] In one implementation, the units 214 may comprise a monitoring unit 216, a graph creation
unit 218, a correlation unit 220 and a group creation unit 222. According to embodiments
of present disclosure, these units 216-222 may comprise hardware components like
processor, microprocessor, microcontrollers, application-specific integrated circuit for
performing various operations of the system 102. It must be understood to a person skilled
in art that the processor 204 may perform all the functions of the units 216-222 according
to various embodiments of the present disclosure.
[0028] Now, referring to figure 1, the environment 100 shows a system 102 that monitors a social
network group 104. The social network group 104 comprises a plurality of members 106AL. The system 102, through its monitoring unit 216 monitors the interaction content 208
of each member of the social network group 104 with other members of the social network
group 104 for a pre-defined time period. In one embodiment, the interaction content 208
comprises chat content 208A and multimedia content 208B shared by each member in the
social network group 104 with other members. The monitored interaction content 208 is
stored by the system 102 in its memory 206 for further use.
[0029] The monitored interaction content 208 saved in the memory 206 is analysed by the graph
creation unit 218 by employing Natural Language Processing (NLP) technique. The
analysis comprises determining from the interaction content 208 of each member, the
various topics that seem to be of interest to the plurality of members 106A-L of the social
network group 104. The topics of interest may comprise a variety of topics including but
not limited to books, movies, politics, science, fashion, beauty, art and travel. The topics
of interest for a member is also determined in conjunction with the member profiles 210
8
pre-stored in the memory 206. Once, the graph creation unit 218 determines the topics of
interest, it then plots interest graphs 108A-L for the plurality of members 106A-L such that
one interest graph is plotted for one member. An interest graph indicates a level of interest
of a member in one or more topics and is created by plotting the one or more topics on the
X-axis and an associated weight for each of the one or more topics on the Y-axis. In one
embodiment, the weight associated with a topic of the one or more topics may be provided
in the form of a numerical value. However, according to another embodiments the weight
associated with a topic of the one or more topics may be provided in the form of other
weighing factors including, but not limited to, grades, percentage etc. An exemplary
illustration of the interest graphs 108 is depicted in figure 3. The interest graphs 108A,
108C, 108F and 108J correspond to members 106A, 106C, 106F and 106J of the social
network group 104. Each of the illustrated interest graphs depict a level of interest of the
members 106A, 106C, 106F and 106J in various topics such as movies, travel, art, fashion,
politics, books and beauty.
[0030] Once, the graph creation unit 218 creates interest graphs 108A-L, the correlation unit 220
correlates interest graph for each member with the interest graphs of other members in
order to determine the members that are interested in a common topic. For instance, with
reference to figure 3, the correlation unit 220 determines that members 106A, 106C, 106F
and 106J have a keen interest in movies. The interest in a particular topic is determined on
the basis of the weight associated with the topic. For instance, in accordance with the
exemplary embodiment, for the correlation unit 220 to establish that “movies” is a common
topic of interest amongst the members 106A, 106C, 106F and 106J, the weight associated
with the topic “movies” has to be greater than a threshold weight, say for example, 4.0 in
the current scenario. However, according to another embodiment, the correlation unit 220
not just determines the common topic of interest but also determines the number of
members interested in that particular topic.
[0031] Further, based on the number of members interested in a common topic, the group creation
unit 222 partitions the social network group 104 into one or more subgroups 110 in such a
manner that each subgroup comprises a set of members interested in a particular common
topic. However, in accordance with the exemplary embodiment, to create a subgroup
9
pertaining to a common topic, it is required that the number of members interested in a
particular topic is greater than or equal to a threshold number of members. For instance, in
accordance with the exemplary embodiment as depicted in figure 1, the plurality of
members 106A-L in the social network group 104 is taken to be 12 and therefore,
accordingly, the threshold number of members for creating a subgroup is taken to be 4 (for
example). However, it may be understood by a skilled person that the threshold number of
members for creating a subgroup can be altered based on the number of members in the
social network group 104.
[0032] Now, in accordance with the exemplary embodiment depicted in figures 1 and 3, since the
number of members interested in the topic “Movies” is equal to the threshold number of
members (i.e., 4), the group creation unit 222 creates a subgroup 110-1 with members
106A, 106C, 106F and 106J.
[0033] Similar methodology may be employed by the system 102 to create other subgroups 110-
2, 110-3 and like (as shown in Fig. 1), where each subgroup comprises a set of members
interested in a particular topic. For instance, like the subgroup 110-1 comprises members
106A, 106C, 106F and 106J with “Movies” as a common topic of interest, the subgroup
110-2 may comprise members 106B, 106E, 106D and 106G with for example, “Politics”
as a common topic of interest and the subgroup 110-3 may comprise members 106L, 106K,
106I and 106H with for example, “Travel” as a common topic of interest.
[0034] In accordance with another embodiment, the system 102 may be configured to further
monitor each of the created subgroups 110 to determine whether any further partitioning is
required within a created subgroup 110. For instance, the subgroup 110-1 comprises
members that are interested in “Movies”. However, the topic of “Movies” is itself a very
broad topic and may contain many genres such as Horror, Thriller, Action, Romance, SciFi etc. So, therefore, it may so happen that the members within the subgroup 110-1 have
interest in different genres (or sub-topics). In such a case, the system 104 would follow the
procedure as described in the preceding paragraphs and further partition the subgroup 110-
1 if the conditions for partitioning – i.e., the weight associated with each of the sub-topics
10
is greater than a threshold weight and/or the number of members interested in the subtopics is greater than a threshold number are met.
[0035] Figure 4 depicts a method 400 for partitioning a social network group 104, in accordance
with an embodiment of the present disclosure. The method 400 may be described in the
general context of computer executable instructions. Generally, computer executable
instructions can include routines, programs, objects, components, data structures,
procedures, modules, and functions, which perform specific functions or implement
specific abstract data types.
[0036] Further, the order in which the method 400 is described is not intended to be construed as
a limitation, and any number of the described method blocks can be combined in any order
to implement the method. Additionally, individual blocks may be deleted from the methods
without departing from the spirit and scope of the subject matter described.
[0037] At block 402, the method 400 may include monitoring interaction content 208 of each
member with other members in the social network group 104 over a predefined time period.
The interaction content 208 comprises at least one of a chat content 208A and a multimedia
content 208B associated with one or more topics, shared by each member while interacting
with the other members.
[0038] At block 404, the method 400 may include analyzing the interaction content 208 by using
Natural Language Processing (NLP) technique for creating a plurality of interest graphs
108A-L corresponding to the plurality of members 106A-L in such a manner that each
interest graph indicates a level of interest of each member against the one or more topics.
[0039] At block 406, the method 400 may include correlating the plurality of interest graphs 108AL with each other in order to identify commonality amongst the plurality of members
106A-L vis-a-vis the one or more topics.
[0040] At block 408, the method 400 may include creating one or more subgroups 110 out of the
social network group 104 in such a manner that each subgroup comprises a set of members,
11
of the plurality of members 106A-L, having commonality in the one or more topics
identified while correlating the plurality of interest graphs 108A-L.
[0041] A description of an embodiment with several components in communication with each
other does not imply that all such components are required. On the contrary, a variety of
optional components are described to illustrate the wide variety of possible embodiments
of the invention.
[0042] When a single device or article is described herein, it will be clear that more than one
device/article (whether they cooperate) may be used in place of a single device/article.
Similarly, where more than one device or article is described herein (whether they
cooperate), it will be clear that a single device/article may be used in place of the more than
one device or article or a different number of devices/articles may be used instead of the
shown number of devices or programs. The functionality and/or the features of a device
may be alternatively embodied by one or more other devices which are not explicitly
described as having such functionality/features. Thus, other embodiments of the invention
need not include the device itself.
[0043] Finally, the language used in the specification has been principally selected for readability
and instructional purposes, and it may not have been selected to delineate or circumscribe
the inventive subject matter. It is therefore intended that the scope of the invention be
limited not by this detailed description, but rather by any claims that issue on an application
based here on. Accordingly, the embodiments of the present invention are intended to be
illustrative, but not limiting, of the scope of the invention, which is set forth in the following
claims.
[0044] While various aspects and embodiments have been disclosed herein, other aspects and
embodiments will be apparent to those skilled in the art. The various aspects and
embodiments disclosed herein are for purposes of illustration and are not intended to be
limiting, with the true scope and spirit being indicated by the following claims.
12
Reference Numerals:
Reference Numeral Description
100
Exemplary environment of a system for partitioning a social network
group
102 System
104 Social Network Group
106/106A-L Plurality of members
108/108A-L Interest Graphs
110/110-1-3 Subgroups
200 Block diagram of the system
202 I/O Interface
204 Processor
206 Memory
208 Interaction Content
208A Chat Content
208B Multimedia Content
210 Member Profile
214 Monitoring Unit
216 Graph Creation Unit
218 Correlation Unit
220 Group Creation Unit
13
300 Exemplary illustration of the interest graphs
400 Method for partitioning a social network group

We Claim

1. A method for partitioning a social network group (104) comprising a plurality of members
(106A-L), the method comprising:
monitoring (402) interaction content (208) of each member with other members in the
social network group (104) over a predefined time period, wherein the interaction content (208)
comprises at least one of a chat content (208A) and a multimedia content (208B) associated
with one or more topics, shared by each member while interacting with the other members;
analyzing (404) the interaction content (208) by using Natural Language Processing
(NLP) technique for creating a plurality of interest graphs (108A-L) corresponding to the
plurality of members (106A-L) in such a manner that each interest graph indicates a level of
interest of each member against the one or more topics;
correlating (406) the plurality of interest graphs (108A-L) with each other in order to
identify commonality amongst the plurality of members (106A-L) vis-a-vis the one or more
topics; and
creating (408) one or more subgroups (110) out of the social network group (104) in
such a manner that each subgroup comprises a set of members, of the plurality of members,
having commonality in the one or more topics identified while correlating the plurality of
interest graphs (108A-L).
2. The method as claimed in claim 1, wherein creating the plurality of interest graphs (108A-L)
comprising plotting the one or more topics on x-axis and a weight associated with each of the
one or more topics on y-axis such that the level of interest of each member in the one or more
topics is determined based on the weight associated with the one or more topics.
3. The method as claimed in claim 1, wherein identifying the commonality amongst the plurality
of members (106A-L) vis-a-vis the one or more topics further comprising determining a
number of members interested in the one or more topics.
4. The method as claimed in claim 1, wherein the one or more sub-groups (110) are created when
at least one of following criteria satisfies:
15
the weight associated with each of the one or more topics is greater than a threshold weight;
and
the number of members interested in the one or more topics is greater than a threshold
number.
5. The method as claimed in claim 1, wherein the one or more topics comprises at least one of
books, movies, politics, science, fashion, beauty, art and travel.
6. A system for partitioning a social network group (104) comprising a plurality of members
(106A-L), the system comprising:
a monitoring unit (216) configured to monitor interaction content (208) of each member
with other members in the social network group (104) over a predefined time period, wherein
the interaction content (208) comprises at least one of a chat content (208A) and a multimedia
content (208B) associated with one or more topics, shared by each member while interacting
with the other members;
a graph creation unit (218) configured to analyze the interaction content (208) by using
Natural Language Processing (NLP) technique to create a plurality of interest graphs (108AL) corresponding to the plurality of members (106A-L) in such a manner that each interest
graph indicates a level of interest of each member against the one or more topics;
a correlation unit (220) configured to correlate the plurality of interest graphs (108AL) with each other in order to identify commonality vis-a-vis the plurality of members (106AL) against the one or more topics; and
a group creation unit (222) configured to create one or more subgroups (110) out of the
social network group (104) in such a manner that each subgroup comprises a set of members,
of the plurality of members (106A-L), having commonality in the one or more topics identified
while correlating the plurality of interest graphs (108A-L).
7. The system as claimed in claim 6, wherein the graph creation unit (218) is configured to create
the plurality of interest graphs (108A-L) by plotting the one or more topics on x-axis and a
weight associated with each of the one or more topics on y-axis such that the level of interest
16
of each member in the one or more topics is determined based on the weight associated with
the one or more topics.
8. The system as claimed in claim 6, wherein to identify commonality amongst the plurality of
members vis-a-vis the one or more topics, the correlation unit (220) is further configured to
determine a number of members interested in the one or more topics.
9. The system as claimed in claim 6, wherein the group creation unit (222) is configured to create
one or more sub-groups (110) when at least one of following criteria satisfies:
the weight associated with each of the one or more topics is greater than a threshold weight;
and
a number of members interested in the one or more topics is greater than a threshold
number.
10. The system as claimed in claim 6, wherein the one or more topics comprises at least one of
books, movies, politics, science, fashion, beauty, art and travel.