  Online Social Media (OSM) is a platform through which the users present
themselves to the connected world by means of messaging, posting, reacting,
tagging, and sharing on different contents with also other social activities.
Nowadays, it has a vast impact on various aspects of the industry, business and
society along with on users life. In an OSN platform, reaching the target users
is one of the primary focus for most of the businesses and other organizations.
Identification and recommendation of influenceable targets help to capture the
appropriate audience efficiently and effectively. In this paper, an effective
model has been discussed in egocentric OSN by incorporating an efficient
influence measured Recommendation System in order to generate a list of top
most influenceable target users among all connected network members for any
specific social network user. Firstly the list of interacted network members
has been updated based on all activities. On which the interacted network
members with most similar activities have been recommended based on the
specific influence category with sentiment type. After that, the top most
influenceable network members in the basis of the required amount among those
updated list of interacted network members have been identified with proper
ranking by analyzing the similarity and frequency of their activity contents
with respect to the activity contents of the main user. Through these two
continuous stages, an effective list of top influenceable targets of the main
user has been distinguished from the egocentric view of any social network.
